Overview

Dataset statistics

Number of variables29
Number of observations60
Missing cells36
Missing cells (%)2.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.7 KiB
Average record size in memory234.1 B

Variable types

Numeric9
Categorical20

Alerts

airdate has constant value "2020-12-13" Constant
url has a high cardinality: 60 distinct values High cardinality
name has a high cardinality: 56 distinct values High cardinality
_links_self_href has a high cardinality: 60 distinct values High cardinality
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
season is highly correlated with number and 2 other fieldsHigh correlation
number is highly correlated with seasonHigh correlation
runtime is highly correlated with season and 2 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with season and 2 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with _embedded_show_webChannel and 11 other fieldsHigh correlation
_embedded_show_webChannel is highly correlated with _embedded_show_officialSite and 12 other fieldsHigh correlation
summary is highly correlated with _embedded_show_webChannel and 3 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 13 other fieldsHigh correlation
_embedded_show_type is highly correlated with _embedded_show_webChannel and 4 other fieldsHigh correlation
_embedded_show_status is highly correlated with _embedded_show_summary and 5 other fieldsHigh correlation
url is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_summary and 5 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
name is highly correlated with url and 2 other fieldsHigh correlation
airdate is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
airtime is highly correlated with _embedded_show_officialSite and 8 other fieldsHigh correlation
_links_self_href is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
type is highly correlated with _embedded_show_summary and 5 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
_embedded_show_language is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with _embedded_show_summary and 8 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
id is highly correlated with url and 19 other fieldsHigh correlation
url is highly correlated with id and 26 other fieldsHigh correlation
name is highly correlated with id and 20 other fieldsHigh correlation
season is highly correlated with id and 15 other fieldsHigh correlation
number is highly correlated with id and 16 other fieldsHigh correlation
type is highly correlated with url and 12 other fieldsHigh correlation
airtime is highly correlated with id and 16 other fieldsHigh correlation
airstamp is highly correlated with id and 20 other fieldsHigh correlation
runtime is highly correlated with id and 18 other fieldsHigh correlation
summary is highly correlated with url and 8 other fieldsHigh correlation
_embedded_show_id is highly correlated with id and 20 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 25 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 25 other fieldsHigh correlation
_embedded_show_type is highly correlated with url and 19 other fieldsHigh correlation
_embedded_show_language is highly correlated with url and 19 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_status is highly correlated with url and 14 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with url and 18 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 25 other fieldsHigh correlation
_embedded_show_ended is highly correlated with id and 17 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 25 other fieldsHigh correlation
_embedded_show_weight is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_webChannel is highly correlated with id and 25 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with url and 12 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 26 other fieldsHigh correlation
_embedded_show_updated is highly correlated with id and 16 other fieldsHigh correlation
_links_self_href is highly correlated with id and 26 other fieldsHigh correlation
number has 4 (6.7%) missing values Missing
runtime has 6 (10.0%) missing values Missing
_embedded_show_runtime has 19 (31.7%) missing values Missing
_embedded_show_averageRuntime has 4 (6.7%) missing values Missing
_embedded_show_webChannel has 3 (5.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique

Reproduction

Analysis started2022-05-10 02:10:02.640592
Analysis finished2022-05-10 02:10:42.426655
Duration39.79 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2044621.35
Minimum1956339
Maximum2318103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-05-09T21:10:42.517238image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1956339
5-th percentile1965850.15
Q11984031.25
median1998362.5
Q32071475.25
95-th percentile2256550.6
Maximum2318103
Range361764
Interquartile range (IQR)87444

Descriptive statistics

Standard deviation91960.28183
Coefficient of variation (CV)0.04497668081
Kurtosis1.109236495
Mean2044621.35
Median Absolute Deviation (MAD)25431.5
Skewness1.423134419
Sum122677281
Variance8456693434
MonotonicityNot monotonic
2022-05-09T21:10:42.681015image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21212681
 
1.7%
19850461
 
1.7%
21117051
 
1.7%
19851151
 
1.7%
19644471
 
1.7%
20372791
 
1.7%
19850931
 
1.7%
19830441
 
1.7%
19968161
 
1.7%
19972991
 
1.7%
Other values (50)50
83.3%
ValueCountFrequency (%)
19563391
1.7%
19626741
1.7%
19644471
1.7%
19659241
1.7%
19677561
1.7%
19692281
1.7%
19740511
1.7%
19757441
1.7%
19772501
1.7%
19773211
1.7%
ValueCountFrequency (%)
23181031
1.7%
22747071
1.7%
22673161
1.7%
22559841
1.7%
22346891
1.7%
21956011
1.7%
21785621
1.7%
21761301
1.7%
21659301
1.7%
21260351
1.7%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
https://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazin
 
1
https://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov
 
1
https://www.tvmaze.com/episodes/2111705/world-wonder-ring-stardom-2020-12-13-stardom-road-to-osaka-dream-cinderella-tag-1
 
1
https://www.tvmaze.com/episodes/1985115/redakcia-s03-special-redakcia-news-novogodnij-lokdaun-castnaa-zizn-silovikov-obokrali-specbort
 
1
https://www.tvmaze.com/episodes/1964447/bani-negri-pentru-zile-albe-1x04-ascunzatoarea
 
1
Other values (55)
55 

Length

Max length151
Median length99
Mean length84.2
Min length62

Characters and Unicode

Total characters5052
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazin
2nd rowhttps://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov
3rd rowhttps://www.tvmaze.com/episodes/1956339/hero-return-1x10-episode-10
4th rowhttps://www.tvmaze.com/episodes/1985601/swallowed-star-1x04-episode-4
5th rowhttps://www.tvmaze.com/episodes/2052508/wu-shen-zhu-zai-1x83-episode-83

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazin1
 
1.7%
https://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov1
 
1.7%
https://www.tvmaze.com/episodes/2111705/world-wonder-ring-stardom-2020-12-13-stardom-road-to-osaka-dream-cinderella-tag-11
 
1.7%
https://www.tvmaze.com/episodes/1985115/redakcia-s03-special-redakcia-news-novogodnij-lokdaun-castnaa-zizn-silovikov-obokrali-specbort1
 
1.7%
https://www.tvmaze.com/episodes/1964447/bani-negri-pentru-zile-albe-1x04-ascunzatoarea1
 
1.7%
https://www.tvmaze.com/episodes/2037279/veneno-s01-special-mas-de-veneno-el-documental1
 
1.7%
https://www.tvmaze.com/episodes/1985093/cuzie-pisma-1x21-otnosenia-i-byt-lubov-posle-50-on-brosil-mena-vo-sne1
 
1.7%
https://www.tvmaze.com/episodes/1983044/ultra-galaxy-fight-the-absolute-conspiracy-1x04-part-41
 
1.7%
https://www.tvmaze.com/episodes/1996816/pappas-pojkar-1x04-leos-triangeldrama-med-en-golddigger1
 
1.7%
https://www.tvmaze.com/episodes/1997299/the-george-lucas-talk-show-1x19-episode-xix-investors-meeting1
 
1.7%
Other values (50)50
83.3%

Length

2022-05-09T21:10:42.866566image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazin1
 
1.7%
https://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov1
 
1.7%
https://www.tvmaze.com/episodes/1977321/stjernestov-1x13-episode-131
 
1.7%
https://www.tvmaze.com/episodes/1956339/hero-return-1x10-episode-101
 
1.7%
https://www.tvmaze.com/episodes/1985601/swallowed-star-1x04-episode-41
 
1.7%
https://www.tvmaze.com/episodes/2052508/wu-shen-zhu-zai-1x83-episode-831
 
1.7%
https://www.tvmaze.com/episodes/1965924/new-japan-pro-wrestling-2020-12-13-super-j-cup-20201
 
1.7%
https://www.tvmaze.com/episodes/2012321/mans-diary-2x06-episode-61
 
1.7%
https://www.tvmaze.com/episodes/2071471/youths-in-the-breeze-1x01-the-boy-and-the-cat-011
 
1.7%
https://www.tvmaze.com/episodes/2071472/youths-in-the-breeze-1x02-the-boy-and-the-cat-021
 
1.7%
Other values (50)50
83.3%

Most occurring characters

ValueCountFrequency (%)
e422
 
8.4%
-413
 
8.2%
s321
 
6.4%
t308
 
6.1%
/300
 
5.9%
o269
 
5.3%
a236
 
4.7%
w199
 
3.9%
i180
 
3.6%
p174
 
3.4%
Other values (29)2230
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3464
68.6%
Decimal Number695
 
13.8%
Other Punctuation480
 
9.5%
Dash Punctuation413
 
8.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e422
12.2%
s321
 
9.3%
t308
 
8.9%
o269
 
7.8%
a236
 
6.8%
w199
 
5.7%
i180
 
5.2%
p174
 
5.0%
m170
 
4.9%
d136
 
3.9%
Other values (15)1049
30.3%
Decimal Number
ValueCountFrequency (%)
1156
22.4%
0104
15.0%
295
13.7%
961
 
8.8%
353
 
7.6%
551
 
7.3%
449
 
7.1%
749
 
7.1%
643
 
6.2%
834
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/300
62.5%
.120
 
25.0%
:60
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-413
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3464
68.6%
Common1588
31.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e422
12.2%
s321
 
9.3%
t308
 
8.9%
o269
 
7.8%
a236
 
6.8%
w199
 
5.7%
i180
 
5.2%
p174
 
5.0%
m170
 
4.9%
d136
 
3.9%
Other values (15)1049
30.3%
Common
ValueCountFrequency (%)
-413
26.0%
/300
18.9%
1156
 
9.8%
.120
 
7.6%
0104
 
6.5%
295
 
6.0%
961
 
3.8%
:60
 
3.8%
353
 
3.3%
551
 
3.2%
Other values (4)175
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5052
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e422
 
8.4%
-413
 
8.2%
s321
 
6.4%
t308
 
6.1%
/300
 
5.9%
o269
 
5.3%
a236
 
4.7%
w199
 
3.9%
i180
 
3.6%
p174
 
3.4%
Other values (29)2230
44.1%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct56
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
Episode 10
 
2
Episode 4
 
2
Episode 6
 
2
Episode 3
 
2
Интернет-магазин
 
1
Other values (51)
51 

Length

Max length100
Median length61.5
Mean length22.18333333
Min length5

Characters and Unicode

Total characters1331
Distinct characters119
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)86.7%

Sample

1st rowИнтернет-магазин
2nd row12 выпуск – Гарик Харламов
3rd rowEpisode 10
4th rowEpisode 4
5th rowEpisode 83

Common Values

ValueCountFrequency (%)
Episode 102
 
3.3%
Episode 42
 
3.3%
Episode 62
 
3.3%
Episode 32
 
3.3%
Интернет-магазин1
 
1.7%
Episode 211
 
1.7%
Редакция. News: новогодний локдаун, частная жизнь силовиков, обокрали спецборт1
 
1.7%
Ascunzătoarea1
 
1.7%
Más de Veneno: El documental1
 
1.7%
"Отношения и быт", "Любовь после 50", "Он бросил меня во сне"1
 
1.7%
Other values (46)46
76.7%

Length

2022-05-09T21:10:43.044294image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode17
 
7.2%
the14
 
6.0%
and7
 
3.0%
cat6
 
2.6%
boy6
 
2.6%
44
 
1.7%
13
 
1.3%
el2
 
0.9%
new2
 
0.9%
20202
 
0.9%
Other values (164)172
73.2%

Most occurring characters

ValueCountFrequency (%)
175
 
13.1%
e75
 
5.6%
o60
 
4.5%
a55
 
4.1%
s49
 
3.7%
r45
 
3.4%
i42
 
3.2%
d41
 
3.1%
n38
 
2.9%
E33
 
2.5%
Other values (109)718
53.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter818
61.5%
Uppercase Letter212
 
15.9%
Space Separator175
 
13.1%
Decimal Number74
 
5.6%
Other Punctuation43
 
3.2%
Dash Punctuation4
 
0.3%
Close Punctuation2
 
0.2%
Currency Symbol2
 
0.2%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e75
 
9.2%
o60
 
7.3%
a55
 
6.7%
s49
 
6.0%
r45
 
5.5%
i42
 
5.1%
d41
 
5.0%
n38
 
4.6%
t29
 
3.5%
l28
 
3.4%
Other values (47)356
43.5%
Uppercase Letter
ValueCountFrequency (%)
E33
15.6%
T26
12.3%
H16
 
7.5%
A16
 
7.5%
C14
 
6.6%
N12
 
5.7%
S10
 
4.7%
Y9
 
4.2%
D9
 
4.2%
B9
 
4.2%
Other values (26)58
27.4%
Decimal Number
ValueCountFrequency (%)
018
24.3%
214
18.9%
114
18.9%
36
 
8.1%
46
 
8.1%
56
 
8.1%
65
 
6.8%
73
 
4.1%
81
 
1.4%
91
 
1.4%
Other Punctuation
ValueCountFrequency (%)
,12
27.9%
#9
20.9%
"8
18.6%
:7
16.3%
/2
 
4.7%
'2
 
4.7%
@1
 
2.3%
?1
 
2.3%
.1
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
-3
75.0%
1
 
25.0%
Currency Symbol
ValueCountFrequency (%)
1
50.0%
$1
50.0%
Space Separator
ValueCountFrequency (%)
175
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin798
60.0%
Common301
 
22.6%
Cyrillic232
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e75
 
9.4%
o60
 
7.5%
a55
 
6.9%
s49
 
6.1%
r45
 
5.6%
i42
 
5.3%
d41
 
5.1%
n38
 
4.8%
E33
 
4.1%
t29
 
3.6%
Other values (43)331
41.5%
Cyrillic
ValueCountFrequency (%)
о26
 
11.2%
и18
 
7.8%
н17
 
7.3%
а16
 
6.9%
е14
 
6.0%
с13
 
5.6%
л12
 
5.2%
р12
 
5.2%
к11
 
4.7%
в10
 
4.3%
Other values (30)83
35.8%
Common
ValueCountFrequency (%)
175
58.1%
018
 
6.0%
214
 
4.7%
114
 
4.7%
,12
 
4.0%
#9
 
3.0%
"8
 
2.7%
:7
 
2.3%
36
 
2.0%
46
 
2.0%
Other values (16)32
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1090
81.9%
Cyrillic232
 
17.4%
None7
 
0.5%
Currency Symbols1
 
0.1%
Punctuation1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
175
 
16.1%
e75
 
6.9%
o60
 
5.5%
a55
 
5.0%
s49
 
4.5%
r45
 
4.1%
i42
 
3.9%
d41
 
3.8%
n38
 
3.5%
E33
 
3.0%
Other values (61)477
43.8%
Cyrillic
ValueCountFrequency (%)
о26
 
11.2%
и18
 
7.8%
н17
 
7.3%
а16
 
6.9%
е14
 
6.0%
с13
 
5.6%
л12
 
5.2%
р12
 
5.2%
к11
 
4.7%
в10
 
4.3%
Other values (30)83
35.8%
None
ValueCountFrequency (%)
ė2
28.6%
ø1
14.3%
é1
14.3%
ă1
14.3%
á1
14.3%
É1
14.3%
Currency Symbols
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136.95
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-05-09T21:10:43.183349image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.25
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation507.5498615
Coefficient of variation (CV)3.706096104
Kurtosis11.06706204
Mean136.95
Median Absolute Deviation (MAD)0
Skewness3.563250106
Sum8217
Variance257606.8619
MonotonicityNot monotonic
2022-05-09T21:10:43.291202image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
139
65.0%
26
 
10.0%
36
 
10.0%
20204
 
6.7%
52
 
3.3%
41
 
1.7%
61
 
1.7%
481
 
1.7%
ValueCountFrequency (%)
139
65.0%
26
 
10.0%
36
 
10.0%
41
 
1.7%
52
 
3.3%
61
 
1.7%
481
 
1.7%
20204
 
6.7%
ValueCountFrequency (%)
20204
 
6.7%
481
 
1.7%
61
 
1.7%
52
 
3.3%
41
 
1.7%
36
 
10.0%
26
 
10.0%
139
65.0%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct25
Distinct (%)44.6%
Missing4
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean19.30357143
Minimum1
Maximum340
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-05-09T21:10:43.416193image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q315.5
95-th percentile59
Maximum340
Range339
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation47.44639833
Coefficient of variation (CV)2.457907776
Kurtosis39.32483781
Mean19.30357143
Median Absolute Deviation (MAD)4
Skewness5.917135455
Sum1081
Variance2251.160714
MonotonicityNot monotonic
2022-05-09T21:10:43.548166image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
38
13.3%
47
11.7%
15
 
8.3%
64
 
6.7%
24
 
6.7%
53
 
5.0%
92
 
3.3%
132
 
3.3%
172
 
3.3%
472
 
3.3%
Other values (15)17
28.3%
(Missing)4
 
6.7%
ValueCountFrequency (%)
15
8.3%
24
6.7%
38
13.3%
47
11.7%
53
 
5.0%
64
6.7%
81
 
1.7%
92
 
3.3%
102
 
3.3%
111
 
1.7%
ValueCountFrequency (%)
3401
1.7%
871
1.7%
831
1.7%
511
1.7%
501
1.7%
472
3.3%
281
1.7%
251
1.7%
212
3.3%
191
1.7%

type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
regular
56 
insignificant_special
 
4

Length

Max length21
Median length7
Mean length7.933333333
Min length7

Characters and Unicode

Total characters476
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular56
93.3%
insignificant_special4
 
6.7%

Length

2022-05-09T21:10:43.680886image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:10:43.808548image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular56
93.3%
insignificant_special4
 
6.7%

Most occurring characters

ValueCountFrequency (%)
r112
23.5%
a64
13.4%
e60
12.6%
g60
12.6%
l60
12.6%
u56
11.8%
i20
 
4.2%
n12
 
2.5%
s8
 
1.7%
c8
 
1.7%
Other values (4)16
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter472
99.2%
Connector Punctuation4
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r112
23.7%
a64
13.6%
e60
12.7%
g60
12.7%
l60
12.7%
u56
11.9%
i20
 
4.2%
n12
 
2.5%
s8
 
1.7%
c8
 
1.7%
Other values (3)12
 
2.5%
Connector Punctuation
ValueCountFrequency (%)
_4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin472
99.2%
Common4
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
r112
23.7%
a64
13.6%
e60
12.7%
g60
12.7%
l60
12.7%
u56
11.9%
i20
 
4.2%
n12
 
2.5%
s8
 
1.7%
c8
 
1.7%
Other values (3)12
 
2.5%
Common
ValueCountFrequency (%)
_4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r112
23.5%
a64
13.4%
e60
12.6%
g60
12.6%
l60
12.6%
u56
11.8%
i20
 
4.2%
n12
 
2.5%
s8
 
1.7%
c8
 
1.7%
Other values (4)16
 
3.4%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
2020-12-13
60 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters600
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-13
2nd row2020-12-13
3rd row2020-12-13
4th row2020-12-13
5th row2020-12-13

Common Values

ValueCountFrequency (%)
2020-12-1360
100.0%

Length

2022-05-09T21:10:43.920554image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:10:44.053692image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-1360
100.0%

Most occurring characters

ValueCountFrequency (%)
2180
30.0%
0120
20.0%
-120
20.0%
1120
20.0%
360
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number480
80.0%
Dash Punctuation120
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2180
37.5%
0120
25.0%
1120
25.0%
360
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2180
30.0%
0120
20.0%
-120
20.0%
1120
20.0%
360
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2180
30.0%
0120
20.0%
-120
20.0%
1120
20.0%
360
 
10.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
nan
44 
06:00
10:00
 
3
12:00
 
2
17:00
 
1
Other values (5)

Length

Max length5
Median length3
Mean length3.533333333
Min length3

Characters and Unicode

Total characters212
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)10.0%

Sample

1st rownan
2nd row12:00
3rd row10:00
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
nan44
73.3%
06:005
 
8.3%
10:003
 
5.0%
12:002
 
3.3%
17:001
 
1.7%
21:101
 
1.7%
14:001
 
1.7%
13:001
 
1.7%
22:051
 
1.7%
20:001
 
1.7%

Length

2022-05-09T21:10:44.180257image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:10:44.378355image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan44
73.3%
06:005
 
8.3%
10:003
 
5.0%
12:002
 
3.3%
17:001
 
1.7%
21:101
 
1.7%
14:001
 
1.7%
13:001
 
1.7%
22:051
 
1.7%
20:001
 
1.7%

Most occurring characters

ValueCountFrequency (%)
n88
41.5%
a44
20.8%
039
18.4%
:16
 
7.5%
110
 
4.7%
26
 
2.8%
65
 
2.4%
71
 
0.5%
41
 
0.5%
31
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter132
62.3%
Decimal Number64
30.2%
Other Punctuation16
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
039
60.9%
110
 
15.6%
26
 
9.4%
65
 
7.8%
71
 
1.6%
41
 
1.6%
31
 
1.6%
51
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
n88
66.7%
a44
33.3%
Other Punctuation
ValueCountFrequency (%)
:16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin132
62.3%
Common80
37.7%

Most frequent character per script

Common
ValueCountFrequency (%)
039
48.8%
:16
20.0%
110
 
12.5%
26
 
7.5%
65
 
6.2%
71
 
1.2%
41
 
1.2%
31
 
1.2%
51
 
1.2%
Latin
ValueCountFrequency (%)
n88
66.7%
a44
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n88
41.5%
a44
20.8%
039
18.4%
:16
 
7.5%
110
 
4.7%
26
 
2.8%
65
 
2.4%
71
 
0.5%
41
 
0.5%
31
 
0.5%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct13
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
2020-12-13T12:00:00+00:00
23 
2020-12-13T11:00:00+00:00
2020-12-13T04:00:00+00:00
2020-12-13T17:00:00+00:00
2020-12-13T05:00:00+00:00
Other values (8)
11 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1500
Distinct characters12
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)10.0%

Sample

1st row2020-12-13T00:00:00+00:00
2nd row2020-12-13T00:00:00+00:00
3rd row2020-12-13T02:00:00+00:00
4th row2020-12-13T02:00:00+00:00
5th row2020-12-13T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-13T12:00:00+00:0023
38.3%
2020-12-13T11:00:00+00:008
 
13.3%
2020-12-13T04:00:00+00:007
 
11.7%
2020-12-13T17:00:00+00:006
 
10.0%
2020-12-13T05:00:00+00:005
 
8.3%
2020-12-13T02:00:00+00:003
 
5.0%
2020-12-13T00:00:00+00:002
 
3.3%
2020-12-13T03:00:00+00:001
 
1.7%
2020-12-13T08:00:00+00:001
 
1.7%
2020-12-13T10:10:00+00:001
 
1.7%
Other values (3)3
 
5.0%

Length

2022-05-09T21:10:44.542146image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-13t12:00:00+00:0023
38.3%
2020-12-13t11:00:00+00:008
 
13.3%
2020-12-13t04:00:00+00:007
 
11.7%
2020-12-13t17:00:00+00:006
 
10.0%
2020-12-13t05:00:00+00:005
 
8.3%
2020-12-13t02:00:00+00:003
 
5.0%
2020-12-13t00:00:00+00:002
 
3.3%
2020-12-13t03:00:00+00:001
 
1.7%
2020-12-13t08:00:00+00:001
 
1.7%
2020-12-13t10:10:00+00:001
 
1.7%
Other values (3)3
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0621
41.4%
2207
 
13.8%
:180
 
12.0%
1170
 
11.3%
-120
 
8.0%
360
 
4.0%
T60
 
4.0%
+60
 
4.0%
49
 
0.6%
76
 
0.4%
Other values (2)7
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1080
72.0%
Other Punctuation180
 
12.0%
Dash Punctuation120
 
8.0%
Uppercase Letter60
 
4.0%
Math Symbol60
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0621
57.5%
2207
 
19.2%
1170
 
15.7%
360
 
5.6%
49
 
0.8%
76
 
0.6%
56
 
0.6%
81
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:180
100.0%
Dash Punctuation
ValueCountFrequency (%)
-120
100.0%
Uppercase Letter
ValueCountFrequency (%)
T60
100.0%
Math Symbol
ValueCountFrequency (%)
+60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1440
96.0%
Latin60
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0621
43.1%
2207
 
14.4%
:180
 
12.5%
1170
 
11.8%
-120
 
8.3%
360
 
4.2%
+60
 
4.2%
49
 
0.6%
76
 
0.4%
56
 
0.4%
Latin
ValueCountFrequency (%)
T60
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0621
41.4%
2207
 
13.8%
:180
 
12.0%
1170
 
11.3%
-120
 
8.0%
360
 
4.0%
T60
 
4.0%
+60
 
4.0%
49
 
0.6%
76
 
0.4%
Other values (2)7
 
0.5%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct36
Distinct (%)66.7%
Missing6
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean41.98148148
Minimum4
Maximum184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-05-09T21:10:44.681080image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7
Q114.25
median40
Q355.75
95-th percentile120
Maximum184
Range180
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation35.85794338
Coefficient of variation (CV)0.8541371603
Kurtosis4.025912248
Mean41.98148148
Median Absolute Deviation (MAD)20
Skewness1.747549859
Sum2267
Variance1285.792103
MonotonicityNot monotonic
2022-05-09T21:10:44.837550image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
76
 
10.0%
604
 
6.7%
453
 
5.0%
403
 
5.0%
1203
 
5.0%
502
 
3.3%
202
 
3.3%
432
 
3.3%
252
 
3.3%
191
 
1.7%
Other values (26)26
43.3%
(Missing)6
 
10.0%
ValueCountFrequency (%)
41
 
1.7%
61
 
1.7%
76
10.0%
81
 
1.7%
91
 
1.7%
111
 
1.7%
121
 
1.7%
131
 
1.7%
141
 
1.7%
151
 
1.7%
ValueCountFrequency (%)
1841
 
1.7%
1203
5.0%
1081
 
1.7%
901
 
1.7%
641
 
1.7%
621
 
1.7%
604
6.7%
581
 
1.7%
561
 
1.7%
551
 
1.7%

summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct17
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
nan
44 
<p>Struggling to get any more information from Ashley, Rex turns to a forensic psychologist for answers. A date for trial is set, but Ashley makes a shocking announcement.</p>
 
1
<p>For King &amp; Country, Zach Williams, Mandisa, Chris Tomlin, Hillsong United, Joshua Aaron, The Bonner Family, The Piano Guys, Stephen McWhirter/Jason Clayborn, Phil Wickham, Matt Maher...how's that for a lineup of music artists celebrating Christmas with The Chosen? To honor the birth of Christ, and to commemorate the humble yet history-altering beginnings of The Greatest Story Ever Told, these musicians all performed their favorite Christmas songs, some on the incredible Jerusalem set of Season 2 of The Chosen. Join us on December 13th, where you'll not only see these performances, along with a special presentation of the Christmas short film that launched The Chosen, you'll also see a sneak peek of highlights of Season 2!</p>
 
1
<p>Dr. Guralnik and her patients struggle with the realities of Covid-19.</p>
 
1
<p>Filming for the drama Tamaki and Sogo are co-starring in is going well. However, Sogo continues to worry about his encounter with Tamaki's younger sister, which he hasn't been able to tell anyone about. On the final day of the special unit's joint practice, Tamaki is shocked to discover that Sogo couldn't trust him emough to tell him about Aya.</p>
 
1
Other values (12)
12 

Length

Max length1021
Median length3
Mean length72.45
Min length3

Characters and Unicode

Total characters4347
Distinct characters76
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)26.7%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan44
73.3%
<p>Struggling to get any more information from Ashley, Rex turns to a forensic psychologist for answers. A date for trial is set, but Ashley makes a shocking announcement.</p>1
 
1.7%
<p>For King &amp; Country, Zach Williams, Mandisa, Chris Tomlin, Hillsong United, Joshua Aaron, The Bonner Family, The Piano Guys, Stephen McWhirter/Jason Clayborn, Phil Wickham, Matt Maher...how's that for a lineup of music artists celebrating Christmas with The Chosen? To honor the birth of Christ, and to commemorate the humble yet history-altering beginnings of The Greatest Story Ever Told, these musicians all performed their favorite Christmas songs, some on the incredible Jerusalem set of Season 2 of The Chosen. Join us on December 13th, where you'll not only see these performances, along with a special presentation of the Christmas short film that launched The Chosen, you'll also see a sneak peek of highlights of Season 2!</p>1
 
1.7%
<p>Dr. Guralnik and her patients struggle with the realities of Covid-19.</p>1
 
1.7%
<p>Filming for the drama Tamaki and Sogo are co-starring in is going well. However, Sogo continues to worry about his encounter with Tamaki's younger sister, which he hasn't been able to tell anyone about. On the final day of the special unit's joint practice, Tamaki is shocked to discover that Sogo couldn't trust him emough to tell him about Aya.</p>1
 
1.7%
<p>The TikTok mansion plays a wild game of Kiss or Truth.</p>1
 
1.7%
<p>The crew meets their nemesis face to tentacle, and the Grand Minister of Agriculture tries the diplomatic approach…key word tries.</p>1
 
1.7%
<p>Ashley's new daughter arrives, but their time together is cut short when Ashley is remanded into custody. Rex and the prosecution engage in one final battle over Ashley's freedom.</p>1
 
1.7%
<p>Rex searches for evidence to implicate Kennard in the crime. Details of Ashley and Kennard's past reveal why she might be covering up for him. Kennard finally breaks his silence.</p>1
 
1.7%
<p>Märtha does not know if she will go home to Norway after the war. Before she can start a new life, she must fight one last battle.</p>1
 
1.7%
Other values (7)7
 
11.7%

Length

2022-05-09T21:10:45.158929image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan44
 
6.1%
the31
 
4.3%
to22
 
3.1%
of17
 
2.4%
and14
 
1.9%
a13
 
1.8%
for7
 
1.0%
on7
 
1.0%
that7
 
1.0%
is7
 
1.0%
Other values (418)552
76.6%

Most occurring characters

ValueCountFrequency (%)
661
15.2%
e377
 
8.7%
n306
 
7.0%
a289
 
6.6%
t267
 
6.1%
o237
 
5.5%
i225
 
5.2%
r202
 
4.6%
s199
 
4.6%
h178
 
4.1%
Other values (66)1406
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3209
73.8%
Space Separator661
 
15.2%
Uppercase Letter259
 
6.0%
Other Punctuation127
 
2.9%
Math Symbol64
 
1.5%
Decimal Number12
 
0.3%
Dash Punctuation8
 
0.2%
Close Punctuation3
 
0.1%
Open Punctuation3
 
0.1%
Initial Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e377
11.7%
n306
 
9.5%
a289
 
9.0%
t267
 
8.3%
o237
 
7.4%
i225
 
7.0%
r202
 
6.3%
s199
 
6.2%
h178
 
5.5%
l135
 
4.2%
Other values (17)794
24.7%
Uppercase Letter
ValueCountFrequency (%)
T33
 
12.7%
A26
 
10.0%
C21
 
8.1%
S17
 
6.6%
O14
 
5.4%
E13
 
5.0%
G13
 
5.0%
R12
 
4.6%
N11
 
4.2%
H11
 
4.2%
Other values (14)88
34.0%
Other Punctuation
ValueCountFrequency (%)
,43
33.9%
.40
31.5%
/17
 
13.4%
'15
 
11.8%
?4
 
3.1%
"2
 
1.6%
;1
 
0.8%
1
 
0.8%
&1
 
0.8%
:1
 
0.8%
Other values (2)2
 
1.6%
Decimal Number
ValueCountFrequency (%)
24
33.3%
13
25.0%
02
16.7%
31
 
8.3%
91
 
8.3%
51
 
8.3%
Math Symbol
ValueCountFrequency (%)
>32
50.0%
<32
50.0%
Space Separator
ValueCountFrequency (%)
661
100.0%
Dash Punctuation
ValueCountFrequency (%)
-8
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3468
79.8%
Common879
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e377
 
10.9%
n306
 
8.8%
a289
 
8.3%
t267
 
7.7%
o237
 
6.8%
i225
 
6.5%
r202
 
5.8%
s199
 
5.7%
h178
 
5.1%
l135
 
3.9%
Other values (41)1053
30.4%
Common
ValueCountFrequency (%)
661
75.2%
,43
 
4.9%
.40
 
4.6%
>32
 
3.6%
<32
 
3.6%
/17
 
1.9%
'15
 
1.7%
-8
 
0.9%
?4
 
0.5%
24
 
0.5%
Other values (15)23
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII4344
99.9%
Punctuation2
 
< 0.1%
None1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
661
15.2%
e377
 
8.7%
n306
 
7.0%
a289
 
6.7%
t267
 
6.1%
o237
 
5.5%
i225
 
5.2%
r202
 
4.7%
s199
 
4.6%
h178
 
4.1%
Other values (63)1403
32.3%
Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
ä1
100.0%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47277.31667
Minimum12906
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-05-09T21:10:45.329652image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum12906
5-th percentile24859.5
Q143190.5
median51682.5
Q352978
95-th percentile59425.65
Maximum61755
Range48849
Interquartile range (IQR)9787.5

Descriptive statistics

Standard deviation10239.03495
Coefficient of variation (CV)0.2165739444
Kurtosis2.058347153
Mean47277.31667
Median Absolute Deviation (MAD)3448.5
Skewness-1.434617756
Sum2836639
Variance104837836.7
MonotonicityNot monotonic
2022-05-09T21:10:45.500616image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
547626
 
10.0%
527724
 
6.7%
440573
 
5.0%
524233
 
5.0%
381991
 
1.7%
521481
 
1.7%
523031
 
1.7%
527371
 
1.7%
528581
 
1.7%
533381
 
1.7%
Other values (38)38
63.3%
ValueCountFrequency (%)
129061
1.7%
187521
1.7%
228931
1.7%
249631
1.7%
306061
1.7%
322141
1.7%
334631
1.7%
349011
1.7%
369071
1.7%
381991
1.7%
ValueCountFrequency (%)
617551
 
1.7%
602461
 
1.7%
599511
 
1.7%
593981
 
1.7%
583561
 
1.7%
578741
 
1.7%
547626
10.0%
540331
 
1.7%
537351
 
1.7%
533381
 
1.7%

_embedded_show_url
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
https://www.tvmaze.com/shows/54762/youths-in-the-breeze
https://www.tvmaze.com/shows/52772/accused-a-mother-on-trial
 
4
https://www.tvmaze.com/shows/44057/hjerteslag
 
3
https://www.tvmaze.com/shows/52423/aukrust-gud-velsigne-var-herre
 
3
https://www.tvmaze.com/shows/38199/fiksiki
 
1
Other values (43)
43 

Length

Max length77
Median length61
Mean length51.1
Min length41

Characters and Unicode

Total characters3066
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)73.3%

Sample

1st rowhttps://www.tvmaze.com/shows/38199/fiksiki
2nd rowhttps://www.tvmaze.com/shows/47865/a-seba-znau
3rd rowhttps://www.tvmaze.com/shows/51471/hero-return
4th rowhttps://www.tvmaze.com/shows/52178/swallowed-star
5th rowhttps://www.tvmaze.com/shows/54033/wu-shen-zhu-zai

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/54762/youths-in-the-breeze6
 
10.0%
https://www.tvmaze.com/shows/52772/accused-a-mother-on-trial4
 
6.7%
https://www.tvmaze.com/shows/44057/hjerteslag3
 
5.0%
https://www.tvmaze.com/shows/52423/aukrust-gud-velsigne-var-herre3
 
5.0%
https://www.tvmaze.com/shows/38199/fiksiki1
 
1.7%
https://www.tvmaze.com/shows/52148/ultra-galaxy-fight-the-absolute-conspiracy1
 
1.7%
https://www.tvmaze.com/shows/52303/pappas-pojkar1
 
1.7%
https://www.tvmaze.com/shows/52737/the-george-lucas-talk-show1
 
1.7%
https://www.tvmaze.com/shows/52858/laikykites-ten1
 
1.7%
https://www.tvmaze.com/shows/53338/el-anesa-farah1
 
1.7%
Other values (38)38
63.3%

Length

2022-05-09T21:10:45.657459image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/54762/youths-in-the-breeze6
 
10.0%
https://www.tvmaze.com/shows/52772/accused-a-mother-on-trial4
 
6.7%
https://www.tvmaze.com/shows/44057/hjerteslag3
 
5.0%
https://www.tvmaze.com/shows/52423/aukrust-gud-velsigne-var-herre3
 
5.0%
https://www.tvmaze.com/shows/34901/sammy-j1
 
1.7%
https://www.tvmaze.com/shows/47865/a-seba-znau1
 
1.7%
https://www.tvmaze.com/shows/51471/hero-return1
 
1.7%
https://www.tvmaze.com/shows/52178/swallowed-star1
 
1.7%
https://www.tvmaze.com/shows/54033/wu-shen-zhu-zai1
 
1.7%
https://www.tvmaze.com/shows/24963/new-japan-pro-wrestling1
 
1.7%
Other values (38)38
63.3%

Most occurring characters

ValueCountFrequency (%)
/300
 
9.8%
w252
 
8.2%
t243
 
7.9%
s238
 
7.8%
o173
 
5.6%
e172
 
5.6%
h160
 
5.2%
m139
 
4.5%
a136
 
4.4%
.120
 
3.9%
Other values (29)1133
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2174
70.9%
Other Punctuation480
 
15.7%
Decimal Number304
 
9.9%
Dash Punctuation108
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w252
11.6%
t243
11.2%
s238
10.9%
o173
 
8.0%
e172
 
7.9%
h160
 
7.4%
m139
 
6.4%
a136
 
6.3%
c86
 
4.0%
p75
 
3.4%
Other values (15)500
23.0%
Decimal Number
ValueCountFrequency (%)
546
15.1%
245
14.8%
445
14.8%
336
11.8%
733
10.9%
926
8.6%
120
6.6%
619
6.2%
017
 
5.6%
817
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/300
62.5%
.120
 
25.0%
:60
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2174
70.9%
Common892
29.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
w252
11.6%
t243
11.2%
s238
10.9%
o173
 
8.0%
e172
 
7.9%
h160
 
7.4%
m139
 
6.4%
a136
 
6.3%
c86
 
4.0%
p75
 
3.4%
Other values (15)500
23.0%
Common
ValueCountFrequency (%)
/300
33.6%
.120
 
13.5%
-108
 
12.1%
:60
 
6.7%
546
 
5.2%
245
 
5.0%
445
 
5.0%
336
 
4.0%
733
 
3.7%
926
 
2.9%
Other values (4)73
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/300
 
9.8%
w252
 
8.2%
t243
 
7.9%
s238
 
7.8%
o173
 
5.6%
e172
 
5.6%
h160
 
5.2%
m139
 
4.5%
a136
 
4.4%
.120
 
3.9%
Other values (29)1133
37.0%

_embedded_show_name
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
Youths in the Breeze
Accused: A Mother on Trial
 
4
Hjerteslag
 
3
Aukrust - Gud velsigne vår Herre
 
3
Фиксики
 
1
Other values (43)
43 

Length

Max length43
Median length24
Mean length16.53333333
Min length6

Characters and Unicode

Total characters992
Distinct characters103
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)73.3%

Sample

1st rowФиксики
2nd rowЯ СЕБЯ ЗНАЮ!
3rd rowHero Return
4th rowSwallowed Star
5th rowWu Shen Zhu Zai

Common Values

ValueCountFrequency (%)
Youths in the Breeze6
 
10.0%
Accused: A Mother on Trial4
 
6.7%
Hjerteslag3
 
5.0%
Aukrust - Gud velsigne vår Herre3
 
5.0%
Фиксики1
 
1.7%
Ultra Galaxy Fight: The Absolute Conspiracy1
 
1.7%
Pappas pojkar1
 
1.7%
The George Lucas Talk Show1
 
1.7%
Laikykitės Ten1
 
1.7%
El Anesa Farah1
 
1.7%
Other values (38)38
63.3%

Length

2022-05-09T21:10:45.804648image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the10
 
5.8%
youths6
 
3.5%
breeze6
 
3.5%
in6
 
3.5%
mother5
 
2.9%
accused4
 
2.3%
a4
 
2.3%
on4
 
2.3%
trial4
 
2.3%
gud3
 
1.8%
Other values (107)119
69.6%

Most occurring characters

ValueCountFrequency (%)
111
 
11.2%
e105
 
10.6%
r58
 
5.8%
n51
 
5.1%
t48
 
4.8%
a45
 
4.5%
s43
 
4.3%
o43
 
4.3%
i42
 
4.2%
u33
 
3.3%
Other values (93)413
41.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter705
71.1%
Uppercase Letter150
 
15.1%
Space Separator111
 
11.2%
Other Punctuation14
 
1.4%
Decimal Number4
 
0.4%
Dash Punctuation3
 
0.3%
Close Punctuation2
 
0.2%
Currency Symbol2
 
0.2%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e105
14.9%
r58
 
8.2%
n51
 
7.2%
t48
 
6.8%
a45
 
6.4%
s43
 
6.1%
o43
 
6.1%
i42
 
6.0%
u33
 
4.7%
h31
 
4.4%
Other values (40)206
29.2%
Uppercase Letter
ValueCountFrequency (%)
A17
 
11.3%
T14
 
9.3%
S10
 
6.7%
M10
 
6.7%
B10
 
6.7%
H9
 
6.0%
W6
 
4.0%
Y6
 
4.0%
L5
 
3.3%
O5
 
3.3%
Other values (28)58
38.7%
Other Punctuation
ValueCountFrequency (%)
'5
35.7%
:5
35.7%
?1
 
7.1%
@1
 
7.1%
#1
 
7.1%
!1
 
7.1%
Decimal Number
ValueCountFrequency (%)
02
50.0%
31
25.0%
71
25.0%
Currency Symbol
ValueCountFrequency (%)
$1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
111
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin794
80.0%
Common137
 
13.8%
Cyrillic61
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e105
 
13.2%
r58
 
7.3%
n51
 
6.4%
t48
 
6.0%
a45
 
5.7%
s43
 
5.4%
o43
 
5.4%
i42
 
5.3%
u33
 
4.2%
h31
 
3.9%
Other values (44)295
37.2%
Cyrillic
ValueCountFrequency (%)
и7
 
11.5%
к6
 
9.8%
м3
 
4.9%
е3
 
4.9%
о3
 
4.9%
а3
 
4.9%
у3
 
4.9%
с3
 
4.9%
Я2
 
3.3%
я2
 
3.3%
Other values (24)26
42.6%
Common
ValueCountFrequency (%)
111
81.0%
'5
 
3.6%
:5
 
3.6%
-3
 
2.2%
)2
 
1.5%
02
 
1.5%
$1
 
0.7%
?1
 
0.7%
1
 
0.7%
@1
 
0.7%
Other values (5)5
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII921
92.8%
Cyrillic61
 
6.1%
None9
 
0.9%
Currency Symbols1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
 
12.1%
e105
 
11.4%
r58
 
6.3%
n51
 
5.5%
t48
 
5.2%
a45
 
4.9%
s43
 
4.7%
o43
 
4.7%
i42
 
4.6%
u33
 
3.6%
Other values (53)342
37.1%
Cyrillic
ValueCountFrequency (%)
и7
 
11.5%
к6
 
9.8%
м3
 
4.9%
е3
 
4.9%
о3
 
4.9%
а3
 
4.9%
у3
 
4.9%
с3
 
4.9%
Я2
 
3.3%
я2
 
3.3%
Other values (24)26
42.6%
None
ValueCountFrequency (%)
å4
44.4%
á2
22.2%
ö1
 
11.1%
ø1
 
11.1%
ė1
 
11.1%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
Scripted
27 
Documentary
11 
Talk Show
Animation
Reality
Other values (3)

Length

Max length11
Median length9
Mean length8.55
Min length4

Characters and Unicode

Total characters513
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimation
2nd rowTalk Show
3rd rowAnimation
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted27
45.0%
Documentary11
18.3%
Talk Show7
 
11.7%
Animation6
 
10.0%
Reality3
 
5.0%
Sports2
 
3.3%
Game Show2
 
3.3%
News2
 
3.3%

Length

2022-05-09T21:10:45.954084image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:10:46.107635image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted27
39.1%
documentary11
15.9%
show9
 
13.0%
talk7
 
10.1%
animation6
 
8.7%
reality3
 
4.3%
sports2
 
2.9%
game2
 
2.9%
news2
 
2.9%

Most occurring characters

ValueCountFrequency (%)
t49
 
9.6%
e45
 
8.8%
i42
 
8.2%
r40
 
7.8%
S38
 
7.4%
c38
 
7.4%
a29
 
5.7%
p29
 
5.7%
o28
 
5.5%
d27
 
5.3%
Other values (16)148
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter435
84.8%
Uppercase Letter69
 
13.5%
Space Separator9
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t49
11.3%
e45
10.3%
i42
9.7%
r40
9.2%
c38
8.7%
a29
 
6.7%
p29
 
6.7%
o28
 
6.4%
d27
 
6.2%
n23
 
5.3%
Other values (8)85
19.5%
Uppercase Letter
ValueCountFrequency (%)
S38
55.1%
D11
 
15.9%
T7
 
10.1%
A6
 
8.7%
R3
 
4.3%
G2
 
2.9%
N2
 
2.9%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin504
98.2%
Common9
 
1.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t49
 
9.7%
e45
 
8.9%
i42
 
8.3%
r40
 
7.9%
S38
 
7.5%
c38
 
7.5%
a29
 
5.8%
p29
 
5.8%
o28
 
5.6%
d27
 
5.4%
Other values (15)139
27.6%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t49
 
9.6%
e45
 
8.8%
i42
 
8.2%
r40
 
7.8%
S38
 
7.4%
c38
 
7.4%
a29
 
5.7%
p29
 
5.7%
o28
 
5.5%
d27
 
5.3%
Other values (16)148
28.8%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
English
16 
Norwegian
11 
Chinese
10 
Russian
Japanese
Other values (11)
15 

Length

Max length10
Median length7
Mean length7.466666667
Min length6

Characters and Unicode

Total characters448
Distinct characters33
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)13.3%

Sample

1st rowRussian
2nd rowRussian
3rd rowChinese
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
English16
26.7%
Norwegian11
18.3%
Chinese10
16.7%
Russian5
 
8.3%
Japanese3
 
5.0%
Spanish3
 
5.0%
Swedish2
 
3.3%
Arabic2
 
3.3%
Korean1
 
1.7%
Ukrainian1
 
1.7%
Other values (6)6
 
10.0%

Length

2022-05-09T21:10:46.261596image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english16
26.7%
norwegian11
18.3%
chinese10
16.7%
russian5
 
8.3%
japanese3
 
5.0%
spanish3
 
5.0%
swedish2
 
3.3%
arabic2
 
3.3%
korean1
 
1.7%
ukrainian1
 
1.7%
Other values (6)6
 
10.0%

Most occurring characters

ValueCountFrequency (%)
n58
12.9%
i55
12.3%
s46
10.3%
e44
9.8%
a36
 
8.0%
h34
 
7.6%
g28
 
6.2%
r18
 
4.0%
E16
 
3.6%
l16
 
3.6%
Other values (23)97
21.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter388
86.6%
Uppercase Letter60
 
13.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n58
14.9%
i55
14.2%
s46
11.9%
e44
11.3%
a36
9.3%
h34
8.8%
g28
7.2%
r18
 
4.6%
l16
 
4.1%
o14
 
3.6%
Other values (9)39
10.1%
Uppercase Letter
ValueCountFrequency (%)
E16
26.7%
N11
18.3%
C10
16.7%
R6
 
10.0%
S5
 
8.3%
J3
 
5.0%
A2
 
3.3%
K1
 
1.7%
U1
 
1.7%
G1
 
1.7%
Other values (4)4
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Latin448
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n58
12.9%
i55
12.3%
s46
10.3%
e44
9.8%
a36
 
8.0%
h34
 
7.6%
g28
 
6.2%
r18
 
4.0%
E16
 
3.6%
l16
 
3.6%
Other values (23)97
21.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n58
12.9%
i55
12.3%
s46
10.3%
e44
9.8%
a36
 
8.0%
h34
 
7.6%
g28
 
6.2%
r18
 
4.0%
E16
 
3.6%
l16
 
3.6%
Other values (23)97
21.7%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct25
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
[]
14 
['Comedy']
['Drama', 'Fantasy']
['Drama', 'Romance']
['Crime']
Other values (20)
23 

Length

Max length43
Median length33
Mean length14.55
Min length2

Characters and Unicode

Total characters873
Distinct characters33
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)30.0%

Sample

1st row[]
2nd row['Comedy']
3rd row['Action', 'Anime', 'Science-Fiction']
4th row['Anime', 'Science-Fiction']
5th row['Action', 'Adventure', 'Anime', 'Fantasy']

Common Values

ValueCountFrequency (%)
[]14
23.3%
['Comedy']8
13.3%
['Drama', 'Fantasy']6
 
10.0%
['Drama', 'Romance']5
 
8.3%
['Crime']4
 
6.7%
['Family']3
 
5.0%
['Drama']2
 
3.3%
['Comedy', 'Family']1
 
1.7%
['History', 'Sports']1
 
1.7%
['Sports']1
 
1.7%
Other values (15)15
25.0%

Length

2022-05-09T21:10:46.410088image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama20
20.8%
14
14.6%
comedy12
12.5%
fantasy7
 
7.3%
romance6
 
6.2%
crime6
 
6.2%
family5
 
5.2%
anime5
 
5.2%
history3
 
3.1%
action3
 
3.1%
Other values (10)15
15.6%

Most occurring characters

ValueCountFrequency (%)
'164
18.8%
a68
 
7.8%
[60
 
6.9%
]60
 
6.9%
m54
 
6.2%
r44
 
5.0%
e43
 
4.9%
36
 
4.1%
,36
 
4.1%
i35
 
4.0%
Other values (23)273
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter429
49.1%
Other Punctuation200
22.9%
Uppercase Letter85
 
9.7%
Open Punctuation60
 
6.9%
Close Punctuation60
 
6.9%
Space Separator36
 
4.1%
Dash Punctuation3
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a68
15.9%
m54
12.6%
r44
10.3%
e43
10.0%
i35
8.2%
o31
7.2%
y31
7.2%
n31
7.2%
t22
 
5.1%
c19
 
4.4%
Other values (7)51
11.9%
Uppercase Letter
ValueCountFrequency (%)
D20
23.5%
C20
23.5%
F15
17.6%
A9
10.6%
S6
 
7.1%
R6
 
7.1%
H4
 
4.7%
M3
 
3.5%
T1
 
1.2%
W1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
'164
82.0%
,36
 
18.0%
Open Punctuation
ValueCountFrequency (%)
[60
100.0%
Close Punctuation
ValueCountFrequency (%)
]60
100.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin514
58.9%
Common359
41.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a68
13.2%
m54
 
10.5%
r44
 
8.6%
e43
 
8.4%
i35
 
6.8%
o31
 
6.0%
y31
 
6.0%
n31
 
6.0%
t22
 
4.3%
D20
 
3.9%
Other values (17)135
26.3%
Common
ValueCountFrequency (%)
'164
45.7%
[60
 
16.7%
]60
 
16.7%
36
 
10.0%
,36
 
10.0%
-3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'164
18.8%
a68
 
7.8%
[60
 
6.9%
]60
 
6.9%
m54
 
6.2%
r44
 
5.0%
e43
 
4.9%
36
 
4.1%
,36
 
4.1%
i35
 
4.0%
Other values (23)273
31.3%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
Running
31 
Ended
21 
To Be Determined

Length

Max length16
Median length7
Mean length7.5
Min length5

Characters and Unicode

Total characters450
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running31
51.7%
Ended21
35.0%
To Be Determined8
 
13.3%

Length

2022-05-09T21:10:46.586440image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:10:46.737010image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
running31
40.8%
ended21
27.6%
to8
 
10.5%
be8
 
10.5%
determined8
 
10.5%

Most occurring characters

ValueCountFrequency (%)
n122
27.1%
e53
11.8%
d50
11.1%
i39
 
8.7%
R31
 
6.9%
u31
 
6.9%
g31
 
6.9%
E21
 
4.7%
16
 
3.6%
T8
 
1.8%
Other values (6)48
 
10.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter358
79.6%
Uppercase Letter76
 
16.9%
Space Separator16
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n122
34.1%
e53
14.8%
d50
14.0%
i39
 
10.9%
u31
 
8.7%
g31
 
8.7%
o8
 
2.2%
t8
 
2.2%
r8
 
2.2%
m8
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
R31
40.8%
E21
27.6%
T8
 
10.5%
B8
 
10.5%
D8
 
10.5%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin434
96.4%
Common16
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n122
28.1%
e53
12.2%
d50
11.5%
i39
 
9.0%
R31
 
7.1%
u31
 
7.1%
g31
 
7.1%
E21
 
4.8%
T8
 
1.8%
o8
 
1.8%
Other values (5)40
 
9.2%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n122
27.1%
e53
11.8%
d50
11.1%
i39
 
8.7%
R31
 
6.9%
u31
 
6.9%
g31
 
6.9%
E21
 
4.7%
16
 
3.6%
T8
 
1.8%
Other values (6)48
 
10.7%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct17
Distinct (%)41.5%
Missing19
Missing (%)31.7%
Infinite0
Infinite (%)0.0%
Mean39.58536585
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-05-09T21:10:46.853379image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7
Q112
median30
Q350
95-th percentile120
Maximum180
Range175
Interquartile range (IQR)38

Descriptive statistics

Standard deviation37.6476929
Coefficient of variation (CV)0.9510507756
Kurtosis4.408448564
Mean39.58536585
Median Absolute Deviation (MAD)20
Skewness1.929710438
Sum1623
Variance1417.34878
MonotonicityNot monotonic
2022-05-09T21:10:46.974384image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
76
 
10.0%
506
 
10.0%
604
 
6.7%
304
 
6.7%
1203
 
5.0%
123
 
5.0%
453
 
5.0%
202
 
3.3%
402
 
3.3%
61
 
1.7%
Other values (7)7
 
11.7%
(Missing)19
31.7%
ValueCountFrequency (%)
51
 
1.7%
61
 
1.7%
76
10.0%
81
 
1.7%
91
 
1.7%
123
5.0%
151
 
1.7%
202
 
3.3%
221
 
1.7%
251
 
1.7%
ValueCountFrequency (%)
1801
 
1.7%
1203
5.0%
604
6.7%
506
10.0%
453
5.0%
402
 
3.3%
304
6.7%
251
 
1.7%
221
 
1.7%
202
 
3.3%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)60.7%
Missing4
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean39.44642857
Minimum4
Maximum188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-05-09T21:10:47.115909image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile6.75
Q111
median36
Q350
95-th percentile120
Maximum188
Range184
Interquartile range (IQR)39

Descriptive statistics

Standard deviation35.36918003
Coefficient of variation (CV)0.8966383349
Kurtosis5.174889979
Mean39.44642857
Median Absolute Deviation (MAD)22
Skewness1.93658344
Sum2209
Variance1250.978896
MonotonicityNot monotonic
2022-05-09T21:10:47.248632image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
76
 
10.0%
424
 
6.7%
483
 
5.0%
1203
 
5.0%
113
 
5.0%
603
 
5.0%
452
 
3.3%
292
 
3.3%
92
 
3.3%
502
 
3.3%
Other values (24)26
43.3%
(Missing)4
 
6.7%
ValueCountFrequency (%)
41
 
1.7%
51
 
1.7%
61
 
1.7%
76
10.0%
81
 
1.7%
92
 
3.3%
113
5.0%
122
 
3.3%
161
 
1.7%
181
 
1.7%
ValueCountFrequency (%)
1881
 
1.7%
1203
5.0%
971
 
1.7%
691
 
1.7%
641
 
1.7%
603
5.0%
591
 
1.7%
571
 
1.7%
551
 
1.7%
502
3.3%

_embedded_show_premiered
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct40
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
2020-12-13
14 
2020-11-29
2020-11-22
 
3
2019-08-15
 
3
2010-12-13
 
1
Other values (35)
35 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters600
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)60.0%

Sample

1st row2010-12-13
2nd row2020-05-01
3rd row2020-10-18
4th row2020-11-29
5th row2020-03-08

Common Values

ValueCountFrequency (%)
2020-12-1314
23.3%
2020-11-294
 
6.7%
2020-11-223
 
5.0%
2019-08-153
 
5.0%
2010-12-131
 
1.7%
2019-07-241
 
1.7%
2020-04-211
 
1.7%
2020-12-061
 
1.7%
2020-05-041
 
1.7%
2016-09-111
 
1.7%
Other values (30)30
50.0%

Length

2022-05-09T21:10:47.386985image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1314
23.3%
2020-11-294
 
6.7%
2020-11-223
 
5.0%
2019-08-153
 
5.0%
2020-09-011
 
1.7%
2020-05-011
 
1.7%
2020-10-181
 
1.7%
2020-03-081
 
1.7%
2015-01-041
 
1.7%
2019-07-211
 
1.7%
Other values (30)30
50.0%

Most occurring characters

ValueCountFrequency (%)
0143
23.8%
2138
23.0%
-120
20.0%
1107
17.8%
925
 
4.2%
320
 
3.3%
513
 
2.2%
812
 
2.0%
48
 
1.3%
68
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number480
80.0%
Dash Punctuation120
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0143
29.8%
2138
28.7%
1107
22.3%
925
 
5.2%
320
 
4.2%
513
 
2.7%
812
 
2.5%
48
 
1.7%
68
 
1.7%
76
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
-120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0143
23.8%
2138
23.0%
-120
20.0%
1107
17.8%
925
 
4.2%
320
 
3.3%
513
 
2.2%
812
 
2.0%
48
 
1.3%
68
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0143
23.8%
2138
23.0%
-120
20.0%
1107
17.8%
925
 
4.2%
320
 
3.3%
513
 
2.2%
812
 
2.0%
48
 
1.3%
68
 
1.3%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
nan
39 
2020-12-13
10 
2020-12-22
2020-12-24
 
1
2020-12-27
 
1
Other values (3)
 
3

Length

Max length10
Median length3
Mean length5.45
Min length3

Characters and Unicode

Total characters327
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)8.3%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan39
65.0%
2020-12-1310
 
16.7%
2020-12-226
 
10.0%
2020-12-241
 
1.7%
2020-12-271
 
1.7%
2020-10-251
 
1.7%
2021-01-311
 
1.7%
2021-11-281
 
1.7%

Length

2022-05-09T21:10:47.516443image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:10:47.661702image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan39
65.0%
2020-12-1310
 
16.7%
2020-12-226
 
10.0%
2020-12-241
 
1.7%
2020-12-271
 
1.7%
2020-10-251
 
1.7%
2021-01-311
 
1.7%
2021-11-281
 
1.7%

Most occurring characters

ValueCountFrequency (%)
n78
23.9%
276
23.2%
042
12.8%
-42
12.8%
a39
11.9%
135
10.7%
311
 
3.4%
41
 
0.3%
71
 
0.3%
51
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number168
51.4%
Lowercase Letter117
35.8%
Dash Punctuation42
 
12.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
276
45.2%
042
25.0%
135
20.8%
311
 
6.5%
41
 
0.6%
71
 
0.6%
51
 
0.6%
81
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
n78
66.7%
a39
33.3%
Dash Punctuation
ValueCountFrequency (%)
-42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common210
64.2%
Latin117
35.8%

Most frequent character per script

Common
ValueCountFrequency (%)
276
36.2%
042
20.0%
-42
20.0%
135
16.7%
311
 
5.2%
41
 
0.5%
71
 
0.5%
51
 
0.5%
81
 
0.5%
Latin
ValueCountFrequency (%)
n78
66.7%
a39
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n78
23.9%
276
23.2%
042
12.8%
-42
12.8%
a39
11.9%
135
10.7%
311
 
3.4%
41
 
0.3%
71
 
0.3%
51
 
0.3%

_embedded_show_officialSite
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct47
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef
https://www.bbc.co.uk/programmes/p08z34bl
 
4
https://play.tv2.no/programmer/serier/hjerteslag
 
3
https://tv.nrk.no/serie/aukrust-gud-velsigne-vaar-herre
 
3
nan
 
2
Other values (42)
42 

Length

Max length105
Median length58.5
Mean length51.1
Min length3

Characters and Unicode

Total characters3066
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)70.0%

Sample

1st rowhttp://www.fixiki.ru
2nd rowhttps://premier.one/show/11906
3rd rowhttps://v.qq.com/detail/q/q72jd29a3oxflsr.html
4th rowhttps://v.qq.com/detail/3/324olz7ilvo2j5f.html
5th rowhttps://v.qq.com/detail/m/7q544xyrava3vxf.html

Common Values

ValueCountFrequency (%)
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef6
 
10.0%
https://www.bbc.co.uk/programmes/p08z34bl4
 
6.7%
https://play.tv2.no/programmer/serier/hjerteslag3
 
5.0%
https://tv.nrk.no/serie/aukrust-gud-velsigne-vaar-herre3
 
5.0%
nan2
 
3.3%
https://www.youtube.com/channel/UC4g4YABfz_vEwmZLjtF2Zjw1
 
1.7%
http://m-78.jp/galaxy-fight/tac/1
 
1.7%
https://www.discoveryplus.se/program/pappas-pojkar1
 
1.7%
https://www.patrickcotnoir.com/glts1
 
1.7%
http://www.laisves.tv1
 
1.7%
Other values (37)37
61.7%

Length

2022-05-09T21:10:47.854012image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef6
 
10.0%
https://www.bbc.co.uk/programmes/p08z34bl4
 
6.7%
https://play.tv2.no/programmer/serier/hjerteslag3
 
5.0%
https://tv.nrk.no/serie/aukrust-gud-velsigne-vaar-herre3
 
5.0%
nan2
 
3.3%
https://play.tv2.no/programmer/underholdning/huskestue1
 
1.7%
https://v.qq.com/detail/q/q72jd29a3oxflsr.html1
 
1.7%
https://v.qq.com/detail/3/324olz7ilvo2j5f.html1
 
1.7%
https://v.qq.com/detail/m/7q544xyrava3vxf.html1
 
1.7%
http://www.njpw1972.com1
 
1.7%
Other values (37)37
61.7%

Most occurring characters

ValueCountFrequency (%)
/246
 
8.0%
t211
 
6.9%
e190
 
6.2%
s173
 
5.6%
.140
 
4.6%
o129
 
4.2%
h121
 
3.9%
a115
 
3.8%
p114
 
3.7%
r114
 
3.7%
Other values (58)1513
49.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2112
68.9%
Other Punctuation460
 
15.0%
Decimal Number288
 
9.4%
Uppercase Letter104
 
3.4%
Dash Punctuation61
 
2.0%
Math Symbol27
 
0.9%
Connector Punctuation14
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t211
 
10.0%
e190
 
9.0%
s173
 
8.2%
o129
 
6.1%
h121
 
5.7%
a115
 
5.4%
p114
 
5.4%
r114
 
5.4%
i94
 
4.5%
n89
 
4.2%
Other values (16)762
36.1%
Uppercase Letter
ValueCountFrequency (%)
M12
11.5%
N11
10.6%
U10
 
9.6%
T9
 
8.7%
D8
 
7.7%
O7
 
6.7%
X7
 
6.7%
C5
 
4.8%
A5
 
4.8%
F4
 
3.8%
Other values (13)26
25.0%
Decimal Number
ValueCountFrequency (%)
456
19.4%
154
18.8%
353
18.4%
233
11.5%
022
 
7.6%
520
 
6.9%
618
 
6.2%
713
 
4.5%
910
 
3.5%
89
 
3.1%
Other Punctuation
ValueCountFrequency (%)
/246
53.5%
.140
30.4%
:58
 
12.6%
?8
 
1.7%
&7
 
1.5%
%1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
-61
100.0%
Math Symbol
ValueCountFrequency (%)
=27
100.0%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2216
72.3%
Common850
 
27.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t211
 
9.5%
e190
 
8.6%
s173
 
7.8%
o129
 
5.8%
h121
 
5.5%
a115
 
5.2%
p114
 
5.1%
r114
 
5.1%
i94
 
4.2%
n89
 
4.0%
Other values (39)866
39.1%
Common
ValueCountFrequency (%)
/246
28.9%
.140
16.5%
-61
 
7.2%
:58
 
6.8%
456
 
6.6%
154
 
6.4%
353
 
6.2%
233
 
3.9%
=27
 
3.2%
022
 
2.6%
Other values (9)100
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII3066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/246
 
8.0%
t211
 
6.9%
e190
 
6.2%
s173
 
5.6%
.140
 
4.6%
o129
 
4.2%
h121
 
3.9%
a115
 
3.8%
p114
 
3.7%
r114
 
3.7%
Other values (58)1513
49.3%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION

Distinct32
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.31666667
Minimum1
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-05-09T21:10:48.140039image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q111.5
median28.5
Q369.25
95-th percentile83.25
Maximum92
Range91
Interquartile range (IQR)57.75

Descriptive statistics

Standard deviation28.05653594
Coefficient of variation (CV)0.7518500029
Kurtosis-1.11416071
Mean37.31666667
Median Absolute Deviation (MAD)21.5
Skewness0.3928185573
Sum2239
Variance787.169209
MonotonicityNot monotonic
2022-05-09T21:10:48.268992image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
36
 
10.0%
286
 
10.0%
395
 
8.3%
703
 
5.0%
723
 
5.0%
12
 
3.3%
252
 
3.3%
62
 
3.3%
22
 
3.3%
832
 
3.3%
Other values (22)27
45.0%
ValueCountFrequency (%)
12
 
3.3%
22
 
3.3%
36
10.0%
62
 
3.3%
81
 
1.7%
102
 
3.3%
121
 
1.7%
151
 
1.7%
171
 
1.7%
221
 
1.7%
ValueCountFrequency (%)
921
 
1.7%
882
3.3%
832
3.3%
762
3.3%
732
3.3%
723
5.0%
703
5.0%
691
 
1.7%
601
 
1.7%
571
 
1.7%

_embedded_show_webChannel
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)47.4%
Missing3
Missing (%)5.0%
Memory size608.0 B
{'id': 21, 'name': 'YouTube', 'country': None, 'officialSite': 'https://www.youtube.com'}
10 
{'id': 118, 'name': 'Youku', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': None}
{'id': 238, 'name': 'NRK TV', 'country': {'name': 'Norway', 'code': 'NO', 'timezone': 'Europe/Oslo'}, 'officialSite': None}
{'id': 327, 'name': 'TV 2 Play', 'country': {'name': 'Norway', 'code': 'NO', 'timezone': 'Europe/Oslo'}, 'officialSite': None}
{'id': 71, 'name': 'BBC Three', 'country': {'name': 'United Kingdom', 'code': 'GB', 'timezone': 'Europe/London'}, 'officialSite': 'https://www.bbc.co.uk/bbcthree'}
Other values (22)
26 

Length

Max length163
Median length143
Mean length117.3157895
Min length67

Characters and Unicode

Total characters6687
Distinct characters68
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)33.3%

Sample

1st row{'id': 21, 'name': 'YouTube', 'country': None, 'officialSite': 'https://www.youtube.com'}
2nd row{'id': 104, 'name': 'Tencent QQ', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': 'https://v.qq.com/'}
3rd row{'id': 104, 'name': 'Tencent QQ', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': 'https://v.qq.com/'}
4th row{'id': 104, 'name': 'Tencent QQ', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': 'https://v.qq.com/'}
5th row{'id': 160, 'name': 'NJPW World', 'country': {'name': 'Japan', 'code': 'JP', 'timezone': 'Asia/Tokyo'}, 'officialSite': None}

Common Values

ValueCountFrequency (%)
{'id': 21, 'name': 'YouTube', 'country': None, 'officialSite': 'https://www.youtube.com'}10
16.7%
{'id': 118, 'name': 'Youku', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': None}6
 
10.0%
{'id': 238, 'name': 'NRK TV', 'country': {'name': 'Norway', 'code': 'NO', 'timezone': 'Europe/Oslo'}, 'officialSite': None}6
 
10.0%
{'id': 327, 'name': 'TV 2 Play', 'country': {'name': 'Norway', 'code': 'NO', 'timezone': 'Europe/Oslo'}, 'officialSite': None}5
 
8.3%
{'id': 71, 'name': 'BBC Three', 'country': {'name': 'United Kingdom', 'code': 'GB', 'timezone': 'Europe/London'}, 'officialSite': 'https://www.bbc.co.uk/bbcthree'}4
 
6.7%
{'id': 104, 'name': 'Tencent QQ', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': 'https://v.qq.com/'}3
 
5.0%
{'id': 377, 'name': 'ATRESplayer PREMIUM', 'country': {'name': 'Spain', 'code': 'ES', 'timezone': 'Europe/Madrid'}, 'officialSite': None}2
 
3.3%
{'id': 379, 'name': 'Shahid', 'country': None, 'officialSite': None}2
 
3.3%
{'id': 265, 'name': 'ESPN+', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': None}1
 
1.7%
{'id': 315, 'name': 'Showtime on Demand', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': None}1
 
1.7%
Other values (17)17
28.3%
(Missing)3
 
5.0%

Length

2022-05-09T21:10:48.398352image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
name95
 
13.7%
id57
 
8.2%
country57
 
8.2%
officialsite57
 
8.2%
none55
 
7.9%
code38
 
5.5%
timezone38
 
5.5%
tv12
 
1.7%
no11
 
1.6%
norway11
 
1.6%
Other values (103)261
37.7%

Most occurring characters

ValueCountFrequency (%)
'1068
16.0%
635
 
9.5%
e430
 
6.4%
o377
 
5.6%
:363
 
5.4%
i342
 
5.1%
n305
 
4.6%
a257
 
3.8%
t248
 
3.7%
,248
 
3.7%
Other values (58)2414
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3398
50.8%
Other Punctuation1814
27.1%
Space Separator635
 
9.5%
Uppercase Letter483
 
7.2%
Decimal Number158
 
2.4%
Close Punctuation95
 
1.4%
Open Punctuation95
 
1.4%
Connector Punctuation6
 
0.1%
Math Symbol3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e430
12.7%
o377
11.1%
i342
10.1%
n305
 
9.0%
a257
 
7.6%
t248
 
7.3%
c197
 
5.8%
m168
 
4.9%
u141
 
4.1%
d128
 
3.8%
Other values (14)805
23.7%
Uppercase Letter
ValueCountFrequency (%)
N103
21.3%
S96
19.9%
T34
 
7.0%
E27
 
5.6%
A26
 
5.4%
C25
 
5.2%
O23
 
4.8%
Y22
 
4.6%
U19
 
3.9%
B17
 
3.5%
Other values (14)91
18.8%
Decimal Number
ValueCountFrequency (%)
142
26.6%
232
20.3%
326
16.5%
717
10.8%
814
 
8.9%
08
 
5.1%
48
 
5.1%
95
 
3.2%
54
 
2.5%
62
 
1.3%
Other Punctuation
ValueCountFrequency (%)
'1068
58.9%
:363
 
20.0%
,248
 
13.7%
/90
 
5.0%
.45
 
2.5%
Space Separator
ValueCountFrequency (%)
635
100.0%
Close Punctuation
ValueCountFrequency (%)
}95
100.0%
Open Punctuation
ValueCountFrequency (%)
{95
100.0%
Connector Punctuation
ValueCountFrequency (%)
_6
100.0%
Math Symbol
ValueCountFrequency (%)
+3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3881
58.0%
Common2806
42.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e430
 
11.1%
o377
 
9.7%
i342
 
8.8%
n305
 
7.9%
a257
 
6.6%
t248
 
6.4%
c197
 
5.1%
m168
 
4.3%
u141
 
3.6%
d128
 
3.3%
Other values (38)1288
33.2%
Common
ValueCountFrequency (%)
'1068
38.1%
635
22.6%
:363
 
12.9%
,248
 
8.8%
}95
 
3.4%
{95
 
3.4%
/90
 
3.2%
.45
 
1.6%
142
 
1.5%
232
 
1.1%
Other values (10)93
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII6687
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'1068
16.0%
635
 
9.5%
e430
 
6.4%
o377
 
5.6%
:363
 
5.4%
i342
 
5.1%
n305
 
4.6%
a257
 
3.8%
t248
 
3.7%
,248
 
3.7%
Other values (58)2414
36.1%

_embedded_show_dvdCountry
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
nan
59 
{'name': 'Ukraine', 'code': 'UA', 'timezone': 'Europe/Zaporozhye'}
 
1

Length

Max length66
Median length3
Mean length4.05
Min length3

Characters and Unicode

Total characters243
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan59
98.3%
{'name': 'Ukraine', 'code': 'UA', 'timezone': 'Europe/Zaporozhye'}1
 
1.7%

Length

2022-05-09T21:10:48.540597image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:10:48.663942image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan59
90.8%
name1
 
1.5%
ukraine1
 
1.5%
code1
 
1.5%
ua1
 
1.5%
timezone1
 
1.5%
europe/zaporozhye1
 
1.5%

Most occurring characters

ValueCountFrequency (%)
n121
49.8%
a62
25.5%
'12
 
4.9%
e7
 
2.9%
o5
 
2.1%
5
 
2.1%
:3
 
1.2%
r3
 
1.2%
i2
 
0.8%
p2
 
0.8%
Other values (17)21
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter213
87.7%
Other Punctuation18
 
7.4%
Space Separator5
 
2.1%
Uppercase Letter5
 
2.1%
Open Punctuation1
 
0.4%
Close Punctuation1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n121
56.8%
a62
29.1%
e7
 
3.3%
o5
 
2.3%
r3
 
1.4%
i2
 
0.9%
p2
 
0.9%
z2
 
0.9%
m2
 
0.9%
u1
 
0.5%
Other values (6)6
 
2.8%
Other Punctuation
ValueCountFrequency (%)
'12
66.7%
:3
 
16.7%
,2
 
11.1%
/1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
U2
40.0%
Z1
20.0%
E1
20.0%
A1
20.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
{1
100.0%
Close Punctuation
ValueCountFrequency (%)
}1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin218
89.7%
Common25
 
10.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n121
55.5%
a62
28.4%
e7
 
3.2%
o5
 
2.3%
r3
 
1.4%
i2
 
0.9%
p2
 
0.9%
z2
 
0.9%
U2
 
0.9%
m2
 
0.9%
Other values (10)10
 
4.6%
Common
ValueCountFrequency (%)
'12
48.0%
5
20.0%
:3
 
12.0%
,2
 
8.0%
/1
 
4.0%
{1
 
4.0%
}1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII243
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n121
49.8%
a62
25.5%
'12
 
4.9%
e7
 
2.9%
o5
 
2.1%
5
 
2.1%
:3
 
1.2%
r3
 
1.2%
i2
 
0.8%
p2
 
0.8%
Other values (17)21
 
8.6%

_embedded_show_summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct44
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>
nan
<p>A thrilling true crime series following a young mother facing up to 99 years in prison for murder. As the case unravels over 5 years, those closest to her search for the truth.</p>
<p>A relationship drama about two young people who fall in love at a difficult time in life. In the series, we meet Anders and Mio who, after a one night stand, find out that they are pregnant.</p>
 
3
<p>Solan, Ludvig and Reodor were regular companions. Here is the story of the artist who hit the Norwegian people's soul and the hearts of both children and adults.</p>
 
3
Other values (39)
39 

Length

Max length913
Median length431.5
Mean length358.9833333
Min length3

Characters and Unicode

Total characters21539
Distinct characters102
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)65.0%

Sample

1st rownan
2nd rownan
3rd row<p>Zero was mankind's first real superhero. Under his watch, countless other superheros appeared and followed in his footsteps. However, after 5 years of war, Zero disappeared without a trace.<br /><br />(Source: zeroscans)</p>
4th row<p>One day, an unexplained RR virus appeared on the earth, drawing the world into disaster. Infected animals mutated into terrible monsters, invaded massively, and humans built walls around the destruction and established the base city as the last bastion for humans. The suffering that mankind has experienced during this period of time is known as the "Great Nirvana Period." Not only that, Luo Feng not only carried the burden of supporting the family but also to protect the human homeland, for the better survival and development of mankind, together with other justice warriors, to join hands against the fierce monsters. Under the desperate situation of the end, can Luo Feng and other warriors repel monsters and successfully protect the human world?</p>
5th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>

Common Values

ValueCountFrequency (%)
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>6
 
10.0%
nan5
 
8.3%
<p>A thrilling true crime series following a young mother facing up to 99 years in prison for murder. As the case unravels over 5 years, those closest to her search for the truth.</p>4
 
6.7%
<p>A relationship drama about two young people who fall in love at a difficult time in life. In the series, we meet Anders and Mio who, after a one night stand, find out that they are pregnant.</p>3
 
5.0%
<p>Solan, Ludvig and Reodor were regular companions. Here is the story of the artist who hit the Norwegian people's soul and the hearts of both children and adults.</p>3
 
5.0%
<p>Once they were the coolest guys in school. Ten years later, they are still partying as if they were carefree teenagers. Now it's high time for daddy's boys to grow up.</p>1
 
1.7%
<p><b>The George Lucas Talk Show</b>, a long-running cult talk show hosted by Connor Ratliff, as George Lucas, his sidekick Watto (Griffin Newman), and his producer Patrick Cotnoir. They interview guests in a panel format weekly on PlanetScum.</p>1
 
1.7%
<p>A show of intellectual satire. The show discusses national and foreign issues in a witty and biting way, and once a month - a topic prepared in detail by the screenwriters. Since the beginning of the fifth season, three hosts have shared the main wheel: Andrius Tapinas, Ignas Grinevičius, and Irma Bogdanovičiūtė.</p>1
 
1.7%
<p>Farah and Shadi are left to deal with the consequences of their son's kidnapping. Between war and peace, Majed and Dalal rediscover their relationship.</p>1
 
1.7%
<p>In a post-apocalyptic world, alone in a bunker, Alice tries to communicate with the outside through the radio.</p>1
 
1.7%
Other values (34)34
56.7%

Length

2022-05-09T21:10:48.801331image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the247
 
6.9%
and132
 
3.7%
of103
 
2.9%
to100
 
2.8%
a91
 
2.5%
in85
 
2.4%
his39
 
1.1%
who38
 
1.1%
is32
 
0.9%
with31
 
0.9%
Other values (1196)2692
75.0%

Most occurring characters

ValueCountFrequency (%)
3520
16.3%
e1966
 
9.1%
t1475
 
6.8%
a1322
 
6.1%
n1254
 
5.8%
o1227
 
5.7%
i1218
 
5.7%
r1096
 
5.1%
s1022
 
4.7%
h895
 
4.2%
Other values (92)6544
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter16233
75.4%
Space Separator3531
 
16.4%
Uppercase Letter670
 
3.1%
Other Punctuation633
 
2.9%
Math Symbol364
 
1.7%
Dash Punctuation41
 
0.2%
Decimal Number41
 
0.2%
Other Letter8
 
< 0.1%
Open Punctuation7
 
< 0.1%
Close Punctuation7
 
< 0.1%
Other values (3)4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1966
12.1%
t1475
 
9.1%
a1322
 
8.1%
n1254
 
7.7%
o1227
 
7.6%
i1218
 
7.5%
r1096
 
6.8%
s1022
 
6.3%
h895
 
5.5%
d607
 
3.7%
Other values (24)4151
25.6%
Uppercase Letter
ValueCountFrequency (%)
T73
 
10.9%
S64
 
9.6%
J53
 
7.9%
A44
 
6.6%
M37
 
5.5%
X36
 
5.4%
H33
 
4.9%
I27
 
4.0%
L26
 
3.9%
F24
 
3.6%
Other values (17)253
37.8%
Other Punctuation
ValueCountFrequency (%)
,212
33.5%
.186
29.4%
/97
15.3%
"49
 
7.7%
'46
 
7.3%
:24
 
3.8%
!12
 
1.9%
?5
 
0.8%
@1
 
0.2%
#1
 
0.2%
Decimal Number
ValueCountFrequency (%)
911
26.8%
08
19.5%
16
14.6%
25
12.2%
55
12.2%
42
 
4.9%
82
 
4.9%
72
 
4.9%
Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Dash Punctuation
ValueCountFrequency (%)
-31
75.6%
8
 
19.5%
2
 
4.9%
Space Separator
ValueCountFrequency (%)
3520
99.7%
 11
 
0.3%
Math Symbol
ValueCountFrequency (%)
>182
50.0%
<182
50.0%
Open Punctuation
ValueCountFrequency (%)
(6
85.7%
[1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
)6
85.7%
]1
 
14.3%
Currency Symbol
ValueCountFrequency (%)
$1
50.0%
1
50.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16903
78.5%
Common4628
 
21.5%
Han4
 
< 0.1%
Katakana4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1966
11.6%
t1475
 
8.7%
a1322
 
7.8%
n1254
 
7.4%
o1227
 
7.3%
i1218
 
7.2%
r1096
 
6.5%
s1022
 
6.0%
h895
 
5.3%
d607
 
3.6%
Other values (51)4821
28.5%
Common
ValueCountFrequency (%)
3520
76.1%
,212
 
4.6%
.186
 
4.0%
>182
 
3.9%
<182
 
3.9%
/97
 
2.1%
"49
 
1.1%
'46
 
1.0%
-31
 
0.7%
:24
 
0.5%
Other values (23)99
 
2.1%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII21491
99.8%
None27
 
0.1%
Punctuation10
 
< 0.1%
Katakana5
 
< 0.1%
CJK4
 
< 0.1%
Dingbats1
 
< 0.1%
Currency Symbols1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3520
16.4%
e1966
 
9.1%
t1475
 
6.9%
a1322
 
6.2%
n1254
 
5.8%
o1227
 
5.7%
i1218
 
5.7%
r1096
 
5.1%
s1022
 
4.8%
h895
 
4.2%
Other values (69)6496
30.2%
None
ValueCountFrequency (%)
 11
40.7%
ä3
 
11.1%
å2
 
7.4%
Å2
 
7.4%
ö2
 
7.4%
é2
 
7.4%
č2
 
7.4%
ā1
 
3.7%
ė1
 
3.7%
ū1
 
3.7%
Punctuation
ValueCountFrequency (%)
8
80.0%
2
 
20.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Dingbats
ValueCountFrequency (%)
1
100.0%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1632413695
Minimum1603467037
Maximum1651757319
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size608.0 B
2022-05-09T21:10:48.969929image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1603467037
5-th percentile1609075962
Q11618466682
median1631244354
Q31648399598
95-th percentile1651385944
Maximum1651757319
Range48290282
Interquartile range (IQR)29932916.5

Descriptive statistics

Standard deviation15366943.97
Coefficient of variation (CV)0.009413633331
Kurtosis-1.420083807
Mean1632413695
Median Absolute Deviation (MAD)14811932
Skewness-0.1683960482
Sum9.794482172 × 1010
Variance2.36142967 × 1014
MonotonicityNot monotonic
2022-05-09T21:10:49.173388image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
16184666826
 
10.0%
16270500894
 
6.7%
16394889063
 
5.0%
16090759623
 
5.0%
16313009771
 
1.7%
16120609221
 
1.7%
16264292641
 
1.7%
16182435821
 
1.7%
16497746891
 
1.7%
16450396161
 
1.7%
Other values (38)38
63.3%
ValueCountFrequency (%)
16034670371
 
1.7%
16085040201
 
1.7%
16090759623
5.0%
16096167881
 
1.7%
16110394971
 
1.7%
16114368421
 
1.7%
16120609221
 
1.7%
16140384281
 
1.7%
16182435821
 
1.7%
16184666826
10.0%
ValueCountFrequency (%)
16517573191
1.7%
16517491651
1.7%
16514170271
1.7%
16513843081
1.7%
16512600631
1.7%
16512343741
1.7%
16509836761
1.7%
16509088001
1.7%
16500542891
1.7%
16497746891
1.7%

_links_self_href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/2015818
 
1
https://api.tvmaze.com/episodes/2312224
 
1
https://api.tvmaze.com/episodes/2312225
 
1
https://api.tvmaze.com/episodes/2312226
 
1
Other values (55)
55 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2340
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
1.7%
https://api.tvmaze.com/episodes/20158181
 
1.7%
https://api.tvmaze.com/episodes/23122241
 
1.7%
https://api.tvmaze.com/episodes/23122251
 
1.7%
https://api.tvmaze.com/episodes/23122261
 
1.7%
https://api.tvmaze.com/episodes/23122271
 
1.7%
https://api.tvmaze.com/episodes/23122281
 
1.7%
https://api.tvmaze.com/episodes/20875881
 
1.7%
https://api.tvmaze.com/episodes/20060911
 
1.7%
https://api.tvmaze.com/episodes/19955071
 
1.7%
Other values (50)50
83.3%

Length

2022-05-09T21:10:49.375280image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
1.7%
https://api.tvmaze.com/episodes/20158181
 
1.7%
https://api.tvmaze.com/episodes/19725791
 
1.7%
https://api.tvmaze.com/episodes/19640001
 
1.7%
https://api.tvmaze.com/episodes/19954051
 
1.7%
https://api.tvmaze.com/episodes/20077601
 
1.7%
https://api.tvmaze.com/episodes/19857891
 
1.7%
https://api.tvmaze.com/episodes/20396221
 
1.7%
https://api.tvmaze.com/episodes/20396231
 
1.7%
https://api.tvmaze.com/episodes/23244271
 
1.7%
Other values (50)50
83.3%

Most occurring characters

ValueCountFrequency (%)
/240
 
10.3%
p180
 
7.7%
s180
 
7.7%
e180
 
7.7%
t180
 
7.7%
o120
 
5.1%
a120
 
5.1%
i120
 
5.1%
.120
 
5.1%
m120
 
5.1%
Other values (16)780
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1500
64.1%
Other Punctuation420
 
17.9%
Decimal Number420
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p180
12.0%
s180
12.0%
e180
12.0%
t180
12.0%
o120
8.0%
a120
8.0%
i120
8.0%
m120
8.0%
h60
 
4.0%
d60
 
4.0%
Other values (3)180
12.0%
Decimal Number
ValueCountFrequency (%)
283
19.8%
962
14.8%
152
12.4%
045
10.7%
335
8.3%
832
 
7.6%
730
 
7.1%
429
 
6.9%
627
 
6.4%
525
 
6.0%
Other Punctuation
ValueCountFrequency (%)
/240
57.1%
.120
28.6%
:60
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1500
64.1%
Common840
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/240
28.6%
.120
14.3%
283
 
9.9%
962
 
7.4%
:60
 
7.1%
152
 
6.2%
045
 
5.4%
335
 
4.2%
832
 
3.8%
730
 
3.6%
Other values (3)81
 
9.6%
Latin
ValueCountFrequency (%)
p180
12.0%
s180
12.0%
e180
12.0%
t180
12.0%
o120
8.0%
a120
8.0%
i120
8.0%
m120
8.0%
h60
 
4.0%
d60
 
4.0%
Other values (3)180
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/240
 
10.3%
p180
 
7.7%
s180
 
7.7%
e180
 
7.7%
t180
 
7.7%
o120
 
5.1%
a120
 
5.1%
i120
 
5.1%
.120
 
5.1%
m120
 
5.1%
Other values (16)780
33.3%

Interactions

2022-05-09T21:10:38.323183image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:13.425443image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:20.558353image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:23.311696image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:25.962490image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:28.708895image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:32.308238image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:33.904851image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:36.011435image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:39.086327image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:15.037067image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:21.591011image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:24.378819image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:26.879217image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:29.871230image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:32.592233image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:34.650708image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:36.810502image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:39.228235image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:15.728995image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:21.768700image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:24.558152image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:27.058377image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:30.267103image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:32.876719image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:34.822872image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:36.975272image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:39.369570image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:16.685095image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:21.918854image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:24.738750image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:27.225917image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:30.575765image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:32.991436image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:34.989887image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:37.276951image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:39.509062image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:17.508583image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:22.091016image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:24.913521image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:27.384187image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:30.861957image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:33.135787image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:35.158396image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:37.416998image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:39.806050image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:18.443771image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:22.415045image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:25.286204image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:27.791785image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:31.357193image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:33.357605image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:35.444453image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:37.771029image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:39.938339image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:18.807397image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:22.761571image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:25.452533image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:27.981997image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:31.590158image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:33.506273image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:35.600940image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:37.928945image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:40.111944image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:19.360589image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:22.952573image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:25.627212image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:28.322794image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:31.825651image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:33.645483image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:35.742568image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:38.064971image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:40.248764image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:19.905090image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:23.139159image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:25.779287image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:28.502443image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:32.060246image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:33.773067image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:35.877513image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:10:38.187043image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:10:49.537222image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:10:49.883774image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:10:50.449739image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:10:50.980974image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:10:51.923083image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:10:40.592599image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:10:41.593544image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:10:42.039394image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:10:42.221536image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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02121268https://www.tvmaze.com/episodes/2121268/fiksiki-4x17-internet-magazinИнтернет-магазин4.017.0regular2020-12-13nan2020-12-13T00:00:00+00:006.0nan38199https://www.tvmaze.com/shows/38199/fiksikiФиксикиAnimationRussian[]Running6.06.02010-12-13nanhttp://www.fixiki.ru1.0Nonenannan1.631301e+09https://api.tvmaze.com/episodes/1977902
11985046https://www.tvmaze.com/episodes/1985046/a-seba-znau-1x12-12-vypusk-garik-harlamov12 выпуск – Гарик Харламов1.012.0regular2020-12-1312:002020-12-13T00:00:00+00:0090.0nan47865https://www.tvmaze.com/shows/47865/a-seba-znauЯ СЕБЯ ЗНАЮ!Talk ShowRussian['Comedy']RunningNaN69.02020-05-01nanhttps://premier.one/show/1190683.0{'id': 21, 'name': 'YouTube', 'country': None, 'officialSite': 'https://www.youtube.com'}nannan1.651384e+09https://api.tvmaze.com/episodes/2015818
21956339https://www.tvmaze.com/episodes/1956339/hero-return-1x10-episode-10Episode 101.010.0regular2020-12-1310:002020-12-13T02:00:00+00:0015.0nan51471https://www.tvmaze.com/shows/51471/hero-returnHero ReturnAnimationChinese['Action', 'Anime', 'Science-Fiction']Running15.016.02020-10-18nanhttps://v.qq.com/detail/q/q72jd29a3oxflsr.html76.0{'id': 104, 'name': 'Tencent QQ', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': 'https://v.qq.com/'}nan<p>Zero was mankind's first real superhero. Under his watch, countless other superheros appeared and followed in his footsteps. However, after 5 years of war, Zero disappeared without a trace.<br /><br />(Source: zeroscans)</p>1.603467e+09https://api.tvmaze.com/episodes/1964000
31985601https://www.tvmaze.com/episodes/1985601/swallowed-star-1x04-episode-4Episode 41.04.0regular2020-12-1310:002020-12-13T02:00:00+00:00NaNnan52178https://www.tvmaze.com/shows/52178/swallowed-starSwallowed StarAnimationChinese['Anime', 'Science-Fiction']RunningNaN21.02020-11-29nanhttps://v.qq.com/detail/3/324olz7ilvo2j5f.html88.0{'id': 104, 'name': 'Tencent QQ', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': 'https://v.qq.com/'}nan<p>One day, an unexplained RR virus appeared on the earth, drawing the world into disaster. Infected animals mutated into terrible monsters, invaded massively, and humans built walls around the destruction and established the base city as the last bastion for humans. The suffering that mankind has experienced during this period of time is known as the "Great Nirvana Period." Not only that, Luo Feng not only carried the burden of supporting the family but also to protect the human homeland, for the better survival and development of mankind, together with other justice warriors, to join hands against the fierce monsters. Under the desperate situation of the end, can Luo Feng and other warriors repel monsters and successfully protect the human world?</p>1.648371e+09https://api.tvmaze.com/episodes/1995405
42052508https://www.tvmaze.com/episodes/2052508/wu-shen-zhu-zai-1x83-episode-83Episode 831.083.0regular2020-12-1310:002020-12-13T02:00:00+00:008.0nan54033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese['Action', 'Adventure', 'Anime', 'Fantasy']Running8.08.02020-03-08nanhttps://v.qq.com/detail/m/7q544xyrava3vxf.html76.0{'id': 104, 'name': 'Tencent QQ', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': 'https://v.qq.com/'}nan<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1.649423e+09https://api.tvmaze.com/episodes/2007760
51965924https://www.tvmaze.com/episodes/1965924/new-japan-pro-wrestling-2020-12-13-super-j-cup-2020Super J Cup 20202020.087.0regular2020-12-1312:002020-12-13T03:00:00+00:00120.0nan24963https://www.tvmaze.com/shows/24963/new-japan-pro-wrestlingNew Japan Pro WrestlingSportsJapanese[]Running120.097.02015-01-04nanhttp://www.njpw1972.com/60.0{'id': 160, 'name': 'NJPW World', 'country': {'name': 'Japan', 'code': 'JP', 'timezone': 'Asia/Tokyo'}, 'officialSite': None}nan<p><b>New Japan Pro Wrestling</b> (NJPW) is the largest professional wrestling promotion in Japan and the second largest promotion in the world.</p>1.650984e+09https://api.tvmaze.com/episodes/1985789
62012321https://www.tvmaze.com/episodes/2012321/mans-diary-2x06-episode-6Episode 62.06.0regular2020-12-13nan2020-12-13T04:00:00+00:0012.0nan50398https://www.tvmaze.com/shows/50398/mans-diaryMan's DiaryAnimationChinese['Anime', 'Supernatural']Running12.012.02019-07-21nanhttps://www.bilibili.com/bangumi/media/md43146223.0{'id': 51, 'name': 'Bilibili', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': None}nan<p>In the twenty-first century, gods and demons can no longer maintain balance due to the rapid development of human society. In an effort to restore proper order, the gods began to take care of saving the world, for which they sent a group of gods and monsters to the world of people, who must find there the " key " to salvation. Su moting is a girl with the personality of "demon child". When her parents asked her to leave home so that she could become independent and independent, she met the beautiful and charming God of Tianjin and the mysterious demon cat. So begins a new turbulent round of su moting's life.</p><p><br /> </p>1.611039e+09https://api.tvmaze.com/episodes/2039622
72071471https://www.tvmaze.com/episodes/2071471/youths-in-the-breeze-1x01-the-boy-and-the-cat-01THE BOY AND THE CAT #011.01.0regular2020-12-13nan2020-12-13T04:00:00+00:007.0nan54762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese['Drama', 'Fantasy']Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef28.0{'id': 118, 'name': 'Youku', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': None}nan<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1.618467e+09https://api.tvmaze.com/episodes/2039623
82071472https://www.tvmaze.com/episodes/2071472/youths-in-the-breeze-1x02-the-boy-and-the-cat-02THE BOY AND THE CAT #021.02.0regular2020-12-13nan2020-12-13T04:00:00+00:007.0nan54762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese['Drama', 'Fantasy']Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef28.0{'id': 118, 'name': 'Youku', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': None}nan<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1.618467e+09https://api.tvmaze.com/episodes/2324427
92071473https://www.tvmaze.com/episodes/2071473/youths-in-the-breeze-1x03-the-boy-and-the-cat-03THE BOY AND THE CAT #031.03.0regular2020-12-13nan2020-12-13T04:00:00+00:007.0nan54762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese['Drama', 'Fantasy']Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef28.0{'id': 118, 'name': 'Youku', 'country': {'name': 'China', 'code': 'CN', 'timezone': 'Asia/Shanghai'}, 'officialSite': None}nan<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1.618467e+09https://api.tvmaze.com/episodes/2324428

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_webChannel_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
502318103https://www.tvmaze.com/episodes/2318103/bride-of-beirut-2x47-episode-47Episode 472.047.0regular2020-12-13nan2020-12-13T12:00:00+00:0045.0nan61755https://www.tvmaze.com/shows/61755/bride-of-beirutBride of BeirutScriptedArabic['Drama', 'Romance']Running45.0NaN2019-09-01nanhttps://shahid.mbc.net/en/series/Arous%20Beirut-season-1/season-376514-3765156.0{'id': 379, 'name': 'Shahid', 'country': None, 'officialSite': None}nan<p>Living with her aunt, kind-hearted Thourayya leads a simple life, but her world is upended when she crosses paths with the handsome and ambitious Fares.</p>1.650909e+09https://api.tvmaze.com/episodes/1985251
511990374https://www.tvmaze.com/episodes/1990374/fantastico-48x50-edition-of-12132020Edition of 12/13/202048.050.0regular2020-12-13nan2020-12-13T14:00:00+00:00NaNnan36907https://www.tvmaze.com/shows/36907/fantasticoFantásticoNewsPortuguese[]RunningNaNNaN1973-08-05nanhttp://g1.globo.com/fantastico/12.0{'id': 131, 'name': 'Globoplay', 'country': {'name': 'Brazil', 'code': 'BR', 'timezone': 'America/Noronha'}, 'officialSite': None}nannan1.625403e+09https://api.tvmaze.com/episodes/2017664
522165930https://www.tvmaze.com/episodes/2165930/off-topic-2020-12-13-the-nerds-won-261The Nerds Won - #2612020.047.0regular2020-12-13nan2020-12-13T17:00:00+00:00120.0nan18752https://www.tvmaze.com/shows/18752/off-topicOff TopicTalk ShowEnglish['Comedy']Running120.0120.02015-12-06nanhttps://roosterteeth.com/series/off-topic-the-achievement-hunter-podcast39.0{'id': 32, 'name': 'Rooster Teeth', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': None}nan<p>The lads and lasses of Achievement Hunter congregate each week to discuss the important questions in life. Plus drink beer.</p>1.631188e+09https://api.tvmaze.com/episodes/1996798
531985914https://www.tvmaze.com/episodes/1985914/idolish7-2x13-lies-and-formalityLies and Formality2.013.0regular2020-12-13nan2020-12-13T17:00:00+00:0025.0<p>Filming for the drama Tamaki and Sogo are co-starring in is going well. However, Sogo continues to worry about his encounter with Tamaki's younger sister, which he hasn't been able to tell anyone about. On the final day of the special unit's joint practice, Tamaki is shocked to discover that Sogo couldn't trust him emough to tell him about Aya.</p>33463https://www.tvmaze.com/shows/33463/idolish7IDOLiSH7AnimationJapanese['Anime', 'Music']Running25.025.02017-11-02nanhttp://idolish7.com/aninana/29.0Nonenan<p>A group of aspiring idols gather at Takanashi Productions and are entrusted with the company's future. The seven men who have just met represent a variety of totally different personalities. However, they each have their own charm and possess unknown potential as idols. Forming a group, they take their first step together as <b>IDOLiSH7</b>. Their brilliantly shining dancing forms onstage eventually begin captivating the hearts of the people. In the glorious but sometimes harsh world of idols, they aim for the top with dreams in their hearts!</p>1.628688e+09https://api.tvmaze.com/episodes/2092729
542008607https://www.tvmaze.com/episodes/2008607/wwe-untold-1x17-goldbergs-streakGoldberg's Streak1.017.0regular2020-12-13nan2020-12-13T17:00:00+00:00NaNnan42321https://www.tvmaze.com/shows/42321/wwe-untoldWWE UntoldDocumentaryEnglish['Sports']RunningNaNNaN2018-09-15nanhttp://network.wwe.com/shows/original/wwe-untold42.0{'id': 15, 'name': 'WWE Network', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': None}nan<p>WWE Superstars past and present reveal their compelling stories about the most important moments in WWE history.</p>1.619615e+09https://api.tvmaze.com/episodes/1950369
551977561https://www.tvmaze.com/episodes/1977561/peytons-places-2x03-lynn-swannLynn Swann2.03.0regular2020-12-13nan2020-12-13T17:00:00+00:0030.0nan43207https://www.tvmaze.com/shows/43207/peytons-placesPeyton's PlacesDocumentaryEnglish['History', 'Sports']Running30.029.02019-07-29nanhttp://www.espn.com/watch/series/2043dd20-9cc0-4abe-b652-c8e7dfdfefa0/peyton-s-places41.0{'id': 265, 'name': 'ESPN+', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': None}nan<p><b>Peyton's Places</b> offers a fun, insightful tour through 100 years of football, following the sport and the league's rise to an American cultural touchstone. For nearly a year, Manning has crisscrossed the country, visiting the people and places that have played an important part in the making of the NFL—highlighting memorable events, teams, players, and trends over the past century.</p>1.647692e+09https://api.tvmaze.com/episodes/2083331
562274707https://www.tvmaze.com/episodes/2274707/couples-therapy-1x10-episode-10Episode 101.010.0regular2020-12-13nan2020-12-13T17:00:00+00:0060.0<p>Dr. Guralnik and her patients struggle with the realities of Covid-19.</p>43299https://www.tvmaze.com/shows/43299/couples-therapyCouples TherapyDocumentaryEnglish[]Running30.046.02019-09-06nanhttps://www.sho.com/couples-therapy46.0{'id': 315, 'name': 'Showtime on Demand', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': None}nan<p><b>Couples Therapy</b> unlocks a hidden world: other people's relationships. Far from reality-show caricatures, this is true documentary filmmaking that brings viewers into the authentic and visceral experience of weekly therapy with four couples. World-class therapist Dr. Orna Guralnik deftly guides the couples through the minefield of honest confrontation with each other and with themselves, revealing the real-life struggles - and extraordinary breakthroughs - typically hidden behind closed doors.</p>1.647085e+09https://api.tvmaze.com/episodes/1997814
572119095https://www.tvmaze.com/episodes/2119095/the-chosen-s01-special-christmas-with-the-chosenChristmas With The Chosen1.0NaNinsignificant_special2020-12-13nan2020-12-13T17:00:00+00:00108.0<p>For King &amp; Country, Zach Williams, Mandisa, Chris Tomlin, Hillsong United, Joshua Aaron, The Bonner Family, The Piano Guys, Stephen McWhirter/Jason Clayborn, Phil Wickham, Matt Maher...how's that for a lineup of music artists celebrating Christmas with The Chosen? To honor the birth of Christ, and to commemorate the humble yet history-altering beginnings of The Greatest Story Ever Told, these musicians all performed their favorite Christmas songs, some on the incredible Jerusalem set of Season 2 of The Chosen. Join us on December 13th, where you'll not only see these performances, along with a special presentation of the Christmas short film that launched The Chosen, you'll also see a sneak peek of highlights of Season 2!</p>47119https://www.tvmaze.com/shows/47119/the-chosenThe ChosenScriptedEnglish['Drama', 'History']Running50.050.02019-04-19nanhttps://studios.vidangel.com/the-chosen92.0{'id': 388, 'name': 'VidAngel', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': None}nan<p><b>The Chosen</b> is the first-ever-multi-season TV show about the life of Jesus. Created outside of the Hollywood system, The Chosen allows us to see Him through the eyes of those who knew him. No matter where you are at in your journey with Jesus Christ, this TV show is for you.</p>1.639514e+09https://api.tvmaze.com/episodes/1997815
581969228https://www.tvmaze.com/episodes/1969228/til-deg-fra-meg-1x03-episode-3Episode 31.03.0regular2020-12-1322:052020-12-13T21:05:00+00:0029.0nan51894https://www.tvmaze.com/shows/51894/til-deg-fra-megTil deg fra megRealityNorwegian[]To Be Determined30.029.02020-11-29nanhttps://tv.nrk.no/serie/til-deg-fra-meg2.0{'id': 238, 'name': 'NRK TV', 'country': {'name': 'Norway', 'code': 'NO', 'timezone': 'Europe/Oslo'}, 'officialSite': None}nan<p>In this year's Advent series, Per Sundnes meets people who are going to give away a Christmas song. They themselves have experienced more adversity than most of us. Who do they want to give a special Christmas song to?</p>1.608504e+09https://api.tvmaze.com/episodes/1998673
592234689https://www.tvmaze.com/episodes/2234689/one-mo-chance-1x09-new-york-new-yorkNew York, New York1.09.0regular2020-12-1320:002020-12-14T01:00:00+00:0046.0<p>On a journey to find love, Chance invites 15 beautiful "ladies" into his home. Each week he will put the hopefuls through various challenges to test their compatibility among other things. However, with constant infighting between the contestants, will Chance be able to finally find his happily ever after?</p>59398https://www.tvmaze.com/shows/59398/one-mo-chanceOne Mo' ChanceRealityEnglish[]RunningNaN47.02020-10-11nanhttps://www.thezeusnetwork.com/one-mo-chance57.0{'id': 331, 'name': 'Zeus', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': None}nan<p>From the breakdown of his relationship with the mother of his children, to the death of his brother and partner Real," the last few years have been personally tough for Kamal Chance Givens. However, the original Stallionaire is now ready to get back on his horse to give love another shot. During Chance return to reality television we'll watch as he goes it alone to find the true love of his life in this new dating competition series.</p>1.649331e+09https://api.tvmaze.com/episodes/1998674